Senior Executive – Data Analytics

RCSA & Internal Control Analyst

Structural Test Engineer

Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Technology Obsolescence - Task force - Data Specialist (VP1)

Specialist, Application Monitoring & Dashboard Analytics (VP2)

Lead, AI & Data Products (Technical)

Account Manager

Senior Team Lead

Role Description: <ul><li>The Business Intelligence &amp; Insights Consultant will be responsible for designing, developing, and delivering enterprise-level BI dashboards, reports, and analytical solutions.</li><li>The role will focus on translating business requirements into actionable insights using Power BI and other data analytics tools, supporting business functions such as Finance, Procurement, and Human Capital Management (HCM).</li><li>The ideal candidate should have strong technical expertise in Power BI, DAX, SQL, and data modelling, along with the ability to engage with business stakeholders and support data-driven decision-making.</li></ul> Responsibilities: <ul><li>Design, develop, and maintain interactive Power BI dashboards, reports, scorecards, and paginated reports.</li><li>Gather business requirements and translate them into technical specifications and reporting solutions.</li><li>Develop data models, DAX calculations, Power Query transformations, and SQL queries.</li><li>Implement Row-Level Security (RLS), Object-Level Security (OLS), drill-through, and dynamic filtering.</li><li>Analyze business data to identify trends, patterns, anomalies, and actionable insights.</li><li>Develop KPI dashboards and performance tracking reports for business stakeholders.</li><li>Ensure data accuracy, consistency, report performance, and adherence to BI standards.</li><li>Collaborate with Data Engineering teams to validate data pipelines and source-to-report accuracy.</li><li>Support self-service BI adoption by conducting user training and developing documentation.</li><li>Engage with stakeholders, manage reporting requirements, conduct UAT, and continuously improve BI solutions.</li><li>Required Technical Skills</li><li>Strong hands-on experience with Power BI, including dashboards, reports, DAX, and Power Query (M).</li><li>Good knowledge of SQL and data extraction techniques.</li><li>Experience in data modelling, including Star and Snowflake schemas.</li><li>Knowledge of Power BI Service, deployment, RLS, and OLS.</li><li>Experience with KPI reporting, data visualization, and business analytics.</li><li>Advanced Excel skills.</li><li>Exposure to Microsoft Fabric, Azure Synapse, Python, or Tableau is an advantage.</li><li>Familiarity with Finance, Procurement, or HCM data domains is preferred.</li></ul> Requirements: <ul><li>Bachelors degree in IT, Computer Science, Business, Data Analytics, or a related discipline.</li><li>4–7 years of relevant experience in BI development, Power BI reporting, data visualization, or analytics.</li><li>Power BI Data Analyst (PL-300) certification required or to be obtained within 12 months.</li><li>Microsoft Fabric Analytics Engineer (DP-600) certification is preferred.</li></ul> Key Competencies <ul><li>Strong analytical and problem-solving skills.</li><li>Excellent stakeholder management and communication skills.</li><li>Strong attention to detail and data accuracy.</li><li>Ability to translate business requirements into technical solutions.</li><li>Good presentation and data storytelling skills.</li><li>Ability to manage multiple reporting requirements and deadlines.</li><li>Continuous learning and improvement mindset</li></ul>

Role Description: <ul><li>We are looking for an RCSA &amp; Internal Control Analyst to support the rollout and ongoing maintenance of the EMEA Risk and Control Self-Assessment (RCSA) framework and related internal control activities.</li><li>Working alongside the EMEA Risk &amp; Control Manager, the successful candidate will provide day-to-day operational support, including coordination, follow-up, documentation and data consolidation.</li><li>The role will help accelerate the rollout, improve consistency across countries and establish a sustainable long-term operating model, while allowing the EMEA Risk &amp; Control Manager to focus on governance, stakeholder management and overall framework oversight.</li><li>The successful candidate will support the rollout, documentation, testing and maintenance of country-level RCSAs and related internal control activities across EMEA. They will help ensure that risk and control information is accurately collected, structured, tracked and kept up to date in coordination with local stakeholders.</li></ul> Responsibilities: <ul><li>Support the implementation and ongoing development of the EMEA Risk and Control Self-Assessment (RCSA) framework, working with country teams to identify, assess and manage risks in line with the Groups risk management methodology.</li><li>Work collaboratively with stakeholders across a range of business functions, including Operations, Finance, Legal and Health, Safety, Security and Environment (HSSE), to understand local processes, identify potential risks and establish appropriate controls.</li><li>Support the identification and assessment of country-specific risks, documenting existing controls, potential gaps and compensating controls to help ensure risks are appropriately managed.</li><li>Develop and maintain local risk and control registers, ensuring information is accurate, up to date and aligned with regional requirements.</li><li>Work with local stakeholders to harmonise risk management approaches and control frameworks across EMEA, promoting consistency while taking account of country-specific requirements and differences in local maturity.</li><li>Support the implementation of the RCSA framework across EMEA countries, coordinating activities, gathering and consolidating information, monitoring progress and following up with stakeholders to ensure timely completion.</li><li>Support second-line (Line 2) control testing activities, including coordinating evidence collection, reviewing supporting documentation and following up on outstanding information or identified control gaps.</li><li>Contribute to compliance activities, including the ongoing monitoring and documentation of anti-corruption and accounting controls in support of Sapin II requirements.</li><li>Track action plans, remediation activities and outstanding issues, working with local stakeholders to monitor progress, address delays and ensure agreed actions are completed.</li><li>Build effective working relationships across countries and functions, encouraging collaboration, knowledge-sharing and consistent approaches to risk management in an international, matrixed organisation.</li><li>Identify opportunities to improve risk and control processes, documentation and procedures, contributing to the continuous development of a consistent and sustainable EMEA control framework.</li></ul> Requirements: Educational Qualifications <ul><li>A degree or equivalent professional experience in Risk Management, Business, Finance, Compliance or a related discipline would be advantageous.</li><li>Ongoing commitment to training and professional development in risk, compliance and audit processes.</li></ul> Relevant Skills and Experience <ul><li>2–5 years experience in risk management, internal controls, compliance or a related field.</li><li>Experience working with risk and compliance frameworks, including risk identification, assessment and control implementation.</li><li>Experience working in an international business or matrix organisation, engaging stakeholders across multiple countries and functions.</li><li>Good understanding of operational processes and internal controls across different business functions.</li><li>Strong organisational, analytical and communication skills, with the ability to manage multiple priorities and build effective working relationships.</li><li>Confident managing documentation, risk registers, trackers and supporting evidence, with strong attention to detail.</li><li>Able to work autonomously, take ownership of tasks and manage competing deadlines.</li></ul> Personal Characteristics &amp; Behaviours <ul><li>Resilient and adaptable: Comfortable navigating challenges, working through ambiguity and maintaining momentum when faced with competing priorities or differing levels of risk maturity across countries.</li><li>Curious and analytical: Naturally inquisitive, with the confidence to ask questions, challenge assumptions and develop an understanding of risks across different business functions.</li><li>A relationship builder: Able to establish trust, communicate effectively and work collaboratively with stakeholders at different levels and across different countries.</li><li>Structured in approach: Able to bring order to complex or ambiguous situations, organise information clearly and establish consistent ways of working.</li><li>Reliable and accountable: Takes ownership of responsibilities and works closely with the EMEA Risk &amp; Control Manager to support decision-making.</li><li>Collaborative and open-minded: Comfortable working across functions, receptive to different perspectives and motivated to improve how teams work together.</li></ul> Travel Requirements <ul><li>10–20% travel within the country, region and internationally may be required on an ad hoc or regular basis.</li></ul>

Responsibilities: <ul><li>Strategic Governance: Act as the technical lead for manufacturing test processes, coordinating technical quality metrics, systemic defect resolution, and sustaining product integrity across multiple global sites.</li><li>Design Influence: Represent structural test in high-level design reviews, setting DfT standards and negotiating probe access and coverage requirements to reduce risk in NPI and production.</li><li>Operational Leadership: Direct the development and deployment of complex ICT and Flying Probe programs. Oversee the qualification and release of test fixtures and assets, ensuring zero-defect compliance.</li><li>Technical Authority: Perform senior-level code reviews and lead global change control processes (ECOs/deviations) for test program source code and manufacturing recipes.</li><li>System Optimization: Lead the integration of advanced On-Board Programming (OBP) strategies and boundary scan (JTAG) flows into the manufacturing line to improve efficiency and test depth.</li><li>Mentorship &amp; Influence: Define and promote debug methodologies for manufacturing site test engineers; act as the lead interface between and external fixture/hardware vendors.</li><li>Process Scalability: Champion the adoption of automated workflows, version control standards, and statistical process control (SPC) to drive continuous improvement across the global manufacturing footprint.</li></ul> Requirements: <ul><li>Bachelors degree or equivalent experience in Electrical Engineering, Manufacturing Engineering, or a related technical field.</li><li>8+ years of professional experience in structural test development, debug, and release on industry-standard ICT platforms (e.g., Keysight i3070/Series 6 or TRI).</li><li>5+ years of experience with Flying Probe system development (e.g., SPEA FP4080 or equivalent).</li><li>Demonstrated experience leading end-to-end manufacturing test requirements, including program development, fixture procurement, and factory floor correlation.</li><li>Proven experience leading technical projects or providing technical guidance to multi-functional teams or external manufacturing partners.</li></ul>

Responsibilities: Deploy and Land: <ul><li>Own end-to-end delivery of AI and analytics products at stations in your region.</li><li>Cover discovery, scoping, development, integration, user acceptance testing (UAT), hypercare and rollout.</li><li>Embed with operations.</li><li>Participate in business stand-ups.</li><li>Visit the ramp and cargo floor.</li><li>Understand local data realities rather than making assumptions.</li><li>Ship production code in Python and comparable stacks against live flight, cargo, workforce and equipment data.</li><li>Avoid handing over prototypes for someone else to productionise.</li><li>Scale deployment by reducing the cost and time required to deploy solutions across additional stations.</li><li>Achieve this through reusable integrations, configuration and runbooks.</li></ul> Build on the Platform, Not Around It: <ul><li>Consume data through the semantic layer and governed data platform.</li><li>Avoid parallel pipelines, local definitions and workarounds.</li><li>Apply Centre of Excellence (CoE) patterns and guardrails.</li><li>Follow reference architectures, AI registry, human-in-the-loop controls, access and residency rules.</li><li>Integrate GenAI and ML into workflows.</li><li>Implement RAG and retrieval patterns.</li><li>Implement agentic and tool-use patterns.</li><li>Apply evaluation frameworks.</li><li>Establish observability.</li><li>Maintain production cost control.</li></ul> Make Insight Self-Service: <ul><li>Build data products, not report queues.</li><li>Design governed, reusable datasets and semantic models.</li><li>Enable operations teams, airlines and forwarders to answer their own questions.</li><li>Put insight in front of the customer.</li><li>Deliver station and customer-facing analytics.</li><li>Enable natural-language access to operational data.</li><li>Ensure appropriate access, residency and confidentiality controls.</li><li>Design for the user, not the requester.</li><li>Ensure every product identifies the decision it changes and the person responsible for making it.</li><li>Instrument usage.</li><li>Retire products that are not used.</li><li>Consolidate fragmented reporting rather than extending it.</li></ul> Close the Loop: <ul><li>Feed field learnings back.</li><li>Convert integration problems into hardened patterns for the CoE and requirements for the platform team.</li><li>Own adoption and benefits.</li><li>Instrument deployments.</li><li>Track usage and benefits against the business case.</li><li>Report results accurately.</li><li>Be the technical face to the business and customers.</li><li>Translate between operations, the CoE and platform engineering.</li><li>Success in the First 12 Months</li></ul> Requirements: Experience: <ul><li>6+ years of experience in software or ML engineering.</li><li>Experience must include customer-facing or business-embedded delivery.</li><li>Demonstrated track record of scoping and delivering complex systems end to end in ambiguous, fast-moving environments.</li><li>Ability to remain accountable after go-live.</li><li>Production experience with LLM or ML systems.</li><li>Experience with prompt and agent design.</li><li>Experience with RAG.</li><li>Experience with evaluation frameworks.</li><li>Experience with deployment at scale.</li><li>Understanding of how model behaviour influences product experience.</li><li>Strong Python and API development skills.</li><li>Experience with FastAPI or equivalent.</li><li>Comfortable working across backend and frontend development.</li><li>Ability to build a working system independently.</li><li>Practical experience with Docker.</li><li>Practical experience with Kubernetes.</li><li>Practical experience with CI/CD.</li><li>Practical experience with cloud data platforms.</li><li>Experience integrating batch and real-time data against complex enterprise data sources.</li><li>Strong understanding of analytics.</li><li>Experience with semantic and dimensional modelling.</li><li>Knowledge of modern BI.</li><li>Experience designing data products that non-technical and external users can operate independently.</li><li>Aviation, logistics or complex operations experience is advantageous but not mandatory.</li><li>Willingness to learn operations directly from the operational floor is essential.</li></ul> Qualifications: <ul><li>Bachelors, MSc or PhD in Computer Science, Engineering, Mathematics or a related field.</li></ul>

Responsibilities: <ul><li>Own end-to-end delivery of AI and analytics products at stations in your region: discovery, scoping, build, integration, UAT, hypercare and rollout.</li><li>Embed with the operation. Sit in business stand-ups, walk the ramp and the cargo floor, and specify the local data reality rather than assuming it.</li><li>Ship production code in Python and comparable stacks against live flight, cargo, workforce and equipment data, not prototypes handed to someone else to productionise.</li><li>Scale deployment. Reduce cost and time-to-deploy from station N to station N+1 through reusable integrations, configuration and runbooks.</li><li>Consume through the semantic layer and the governed data platform. No parallel pipelines, no local definitions, no workarounds.</li><li>Apply CoE patterns and guardrails: reference architectures, AI registry, human-in-the-loop controls, access and residency rules.</li><li>Integrate GenAI and ML into workflows: RAG and retrieval, agentic and tool-use patterns, evaluation frameworks, observability and cost control in production.</li><li>Build data products, not report queues. Design- governed, reusable datasets and semantic models that let operations, airlines and forwarders answer their own questions.</li><li>Put insight in front of the customer. Deliver station and customer-facing analytics, including natural-language access to operational data, with the access, residency and confidentiality controls customer data demands.</li><li>Design for the user, not the requester. Every product names the decision it changes and who makes it. Instrument usage, retire what nobody opens, consolidate the long tail rather than extend it.&nbsp;</li><li>Feed the field back. Every integration problem you solve becomes a hardened pattern for the CoE and a requirement for the platform team.</li><li>Own adoption and benefits. Instrument what you deploy, track usage and benefit against the business case, and report it honestly.</li><li>Be the technical face to the business and to customers, translating between operations, the CoE and platform engineering.&nbsp;</li></ul> Requirements:&nbsp; <ul><li>6+ years in software or ML engineering, including customer-facing or business-embedded delivery.</li><li>Track record of scoping and shipping complex systems end to end in ambiguous, fast-moving environments, and staying accountable after go-live.</li><li>Production experience with LLM or ML systems: prompt and agent design, RAG, evaluation frameworks, deployment at scale, and an understanding of how model behaviour shapes product experience.</li><li>Strong Python and API development (FastAPI or equivalent); comfortable across backend and front-end enough to build a working system alone.</li><li>Practical depth in Docker, Kubernetes, CI/CD, and cloud data platforms; batch and real-time integration against messy enterprise sources.</li><li>Fluency in the analytics half of the job: semantic and dimensional modelling, modern BI, and designing data products that non-technical and external users can operate without help.</li><li>Aviation, logistics or complex operations exposure is an advantage, not a prerequisite. Willingness to learn the operation from the floor is not optional.</li><li>Bachelors, MSc or PhD in Computer Science, Engineering, Mathematics or related field.&nbsp;</li></ul>

﻿Responsibilities: Data Collection &amp; Integration: Collect and consolidate data from multiple sources, including: <ul><li>CMDB platforms (e.g., Remedy)</li><li>IT Asset Management (ITAM) systems</li><li>Vendor lifecycle and support data</li><li>Security, vulnerability, and patching sources</li><li>Ensure data consistency and alignment across asset, configuration, and lifecycle repositories</li><li>Validate data accuracy, completeness, and currency</li></ul> Technology Obsolescence Analysis: <ul><li>Identify EOL, EOS, and obsolete technologies across hardware, software, OS, databases, middleware, and cloud services</li><li>Analyze lifecycle risks by technology type, vendor, business unit, and criticality</li><li>Support prioritization of remediation based on risk, business impact, and exposure</li></ul> Reporting &amp; Dashboarding: <ul><li>Design, develop, and maintain interactive dashboards and reports using:</li><li>Power BI / Tableau</li></ul> Create Standard Views Covering: <ul><li>Obsolescence risk heatmaps</li><li>Aging and lifecycle timelines</li><li>Remediation progress and trends</li><li>Compliance and audit‑ready metrics</li><li>Enable self‑service analytics for stakeholders where appropriate</li></ul> CMDB &amp; Asset Management Support: <ul><li>Support the alignment of CMDB data with actual deployed assets</li><li>Identify gaps, redundancies, or inaccuracies in configuration and asset records</li><li>Drive improvements in asset lifecycle tagging, ownership, and criticality classification</li><li>Collaborate with ITSM, ITAM, and platform teams to improve data quality and governance</li></ul> Stakeholder &amp; Decision Support: <ul><li>Provide insights and analysis to:</li><li>Domain leads and task force leads</li><li>Project managers and delivery teams</li><li>Risk, security, and audit stakeholders</li><li>Translate complex data into clear, actionable insights for non‑technical audiences</li><li>Support business case development and roadmap planning with data evidence</li></ul> Data Governance &amp; Continuous Improvement: <ul><li>Define and document data definitions, metrics, and reporting standards</li><li>Automate data refreshes and reporting pipelines where possible</li><li>Identify opportunities to improve lifecycle visibility and predictive risk analysis</li></ul> Requirements: <ul><li>5–8+ years of experience in a data analyst or reporting role within IT or technology functions</li><li>Experience supporting modernization, risk, lifecycle, or transformation initiatives is a strong advantage</li><li>Bachelor’s degree in Information Systems, Computer Science, Data Analytics, or related field</li><li>Power BI or Tableau certification</li><li>ITIL or IT Asset Management certification is a plus</li><li>Data &amp; Analytics Skills</li><li>Strong experience in data analysis and visualization</li><li>Hands on expertise in:</li><li>Power BI (DAX, data modeling, performance optimization)</li><li>Tableau (dashboards, calculated fields, storytelling)</li><li>Strong SQL skills for querying large datasets</li><li>Experience working with structured and semi structured data</li></ul>

Responsibilities: <ul><li>Gather and analyze user requirements for dashboard, monitoring, and reporting enhancements.</li><li>Design, develop, and maintain operational dashboards and monitoring solutions based on business and technical requirements.</li><li>Create, modify, and optimize queries to extract, analyze, and present data for business and operational reporting.</li><li>Develop reports and analytics that provide actionable insights into system performance, availability, and operational health.</li><li>Support and administer enterprise monitoring tools such as Splunk and Geneos.</li><li>Troubleshoot monitoring alerts, dashboard discrepancies, and reporting-related issues.</li><li>Participate in system implementation, enhancement, testing, and deployment activities.</li><li>Ensure compliance with organizational standards, governance, and audit requirements.</li><li>Prepare and maintain technical documentation, user guides, and operational procedures.</li><li>To identify area of monitoring coverage to be improved; and work with relevant teams to enable monitoring solution to improve monitoring coverage.</li><li>To identify area of triage efficiency to be improved; and work with relevant teams to implement solution to improve triage efficiency.</li><li>To identify area of automation of service recovery ability to be improved; and work with relevant teams to implement solution to automate service recovery ability.</li><li>To work with various stakeholders (i.e., service automation, level 2 (group) and level 3 production support etc) to implement application monitoring, service end-to-end dashboard, and automation of service recovery.</li></ul> Requirements: <ul><li>Strong hunter mentality with a passion for creating new business opportunities and opening new partner relationships.</li><li>Experience in business development, channel sales, partner sales, technology sales, or customer acquisition roles.</li><li>Comfort with outbound prospecting, cold outreach, networking, pipeline generation, and opportunity development.</li><li>Understanding of cloud technologies, managed services, software licensing, cybersecurity, or broader IT solutions.</li><li>Strong commercial acumen with the ability to influence stakeholders and build strategic business relationships.</li><li>Self-motivated, resilient, and driven by achieving growth targets, partner acquisition goals, and business outcomes.</li></ul>

Role Description: <ul><li>The organization is investing in a small number of high-impact AI and data products intended to operate across its global station network. </li><li>Each requires a single accountable owner who can hold the technical architecture and the product direction together, from first implementation through multi-station scale.</li><li>We are looking for a Lead, AI &amp; Data Products to take that ownership.&nbsp;</li><li>This is a senior individual contributor role for an engineer or applied scientist who has moved into product leadership, not a product manager with adjacent technical exposure.</li><li>You will be expected to reason about model design, data architecture and production trade-offs at the level of the engineers building the system, and to hold the roadmap, business case and stakeholder relationships at the level of the executives funding it.&nbsp;</li><li>The role operates horizontally.</li><li>You will act as the single-threaded owner for assigned initiatives, working with the AI Centre of Excellence on patterns and feasibility, with Data Engineering and Platform on the data foundation, with Operational Excellence and the business product owners on process change, and with the forward deployed engineers in region on station rollout.</li></ul> This is a hands-on role. <ul><li>You will review and contribute to code, make architectural calls, and spend meaningful time at the frontline understanding operations directly rather than through documentation.</li></ul> Responsibilities: Technical product ownership <ul><li>Own the product end to end for assigned AI and data initiatives: discovery, technical architecture, roadmap, delivery sequencing and global rollout readiness.</li><li>Act as single-threaded owner. One person accountable for whether the product works, is adopted, and delivers its business case across stations and regions.</li><li>Convert programs into products.&nbsp;</li><li>Move initiatives currently run as projects onto a product footing with a roadmap, a lifecycle, named users and a benefit measure.</li><li>Make the build decisions: in-house, CoE pattern, capability center, or vendor. Own the trade-off and the consequences.</li></ul> Technical depth <ul><li>Set the architecture for AI and data products spanning forecasting, optimization, simulation, GenAI and agentic workflows, and defend it in technical review.</li><li>Work in the codebase. Review designs and pull requests, prototype where it resolves ambiguity faster than discussion, and contribute directly when delivery depends on it.</li><li>Own production quality: model robustness, explainability, evaluation, monitoring, latency and cost in service, not only at launch.</li><li>Build on the platform. Consume governed data through the semantic layer and apply CoE guardrails rather than constructing parallel capability.</li></ul> Business and delivery leadership <ul><li>Translate operational problems into technical solutions and, equally, translate technical constraints into terms operations and commercial leadership can act on.</li><li>Own the business case with the business product owner: the benefit hypothesis, the measurement approach and the reported outcome.</li><li>Lead without direct authority across engineering, data science, operations and regional teams, including delivery through the capability center and vendor partners.</li><li>Work from the frontline.</li><li>Regular Gemba at stations, with operational understanding built firsthand.</li></ul> Requirements: <ul><li>10+ years in engineering, applied AI or data science, with a substantial portion spent building and running systems in production rather than specifying them.</li><li>Demonstrable record of owning technical products end to end and scaling them beyond a first implementation into multi site or multi-market operation.</li><li>Depth in one or more of: forecasting (time series, probabilistic, hierarchical), optimization (MIP, LP, heuristics), simulation, or production GenAI and agentic systems, with working literacy across the others.</li><li>Strong Python and SQL, with practical command of the modern data and ML stack: cloud data platforms, pipelines, model deployment, evaluation and monitoring.</li><li>Experience influencing senior stakeholders and operating across engineering, operations and commercial functions without direct reporting lines.</li><li>Aviation, logistics or complex physical operations exposure is an advantage, not a prerequisite.</li></ul> Qualifications <ul><li>Bachelors, MSc or PhD in Computer Science, Engineering, Data Science, Mathematics, Operations Research or a related field. Personal characteristics</li><li>Technical credibility earned through building, not through managing builders.</li><li>Judgement on trade-offs between scope, speed and quality, with the confidence to decide under incomplete information.</li><li>Clear communication with engineers, operators and executives, adjusting register without losing precision.</li><li>Comfort with ambiguity and being accountable for outcomes rather than activity.</li></ul>

Responsibilities: <ul><li>Manage key accounts and develop strong relationships with customer stakeholders.</li><li>Identify and pursue business development opportunities to grow revenue in the Aerospace, Defense, and Marine sectors.</li><li>Manage direct global accounts and OEM business.</li><li>Provide technical solutions to government, PSU, and defense-sector customers.</li><li>Manage customer communication and maintain regular contact with key decision-makers.</li><li>Prepare and manage quotations, proposals, offers, and project contracts.</li><li>Lead commercial discussions, pricing, and contract negotiations.</li><li>Collaborate with channel and distribution partners to support business growth.</li><li>Identify customer needs and develop solution-oriented proposals.</li><li>Generate new business opportunities and close direct sales deals.</li></ul> Requirements: <ul><li>B.Tech in Mechanical, Electrical, or Electronics Engineering.</li><li>At least 5 years of relevant experience in a customer-facing role.</li><li>Experience in key account management and business development.</li><li>Proven experience handling direct OEM business.</li><li>Demonstrated success closing direct business deals.</li><li>Experience preparing offers, quotations, proposals, and presentations.</li><li>Proficiency in Microsoft Excel and presentation tools.</li><li>Required Skills and Competencies</li><li>Strong customer relationship management skills.</li><li>Excellent communication and interpersonal skills.</li><li>Strong influencing, selling, and negotiation abilities.</li><li>Solution-oriented approach and basic problem-solving skills.</li><li>Creative approach to identifying business opportunities.</li><li>Resilience and adaptability in a changing business environment.</li><li>Ability to work effectively with customers, internal teams, and channel partners.</li></ul>

Responsibilities: <ul><li>Lead &amp; participate in the design, development, and maintenance of FMF-related applications.&nbsp;&nbsp;</li><li>Conduct impact analysis and internal data mapping during the design phase.&nbsp;&nbsp;</li><li>Collaborate with business analysts and stakeholders to finalize technical requirements.&nbsp;&nbsp;</li><li>Perform defect analysis and resolution.&nbsp;&nbsp;</li><li>Write and maintain Unix/Linux shell scripts to support automation and integration.&nbsp;&nbsp;</li><li>Execute SQL queries and updates to support application logic and reporting.&nbsp;&nbsp;</li><li>Manage and mentor junior developers, ensuring quality and timely delivery.&nbsp;&nbsp;</li><li>Coordinate with testing, infrastructure, and compliance teams to ensure smooth deployment and support.&nbsp;&nbsp;</li><li>Provide regular updates to project managers and escalate risks/issues with proposed resolutions.&nbsp;&nbsp;</li><li>Lead technical implementation of vendor products (e.g., Firco™ Continuity).&nbsp;&nbsp;</li><li>Perform gap analysis between internal requirements and vendor product capabilities.&nbsp;&nbsp;</li><li>Liaise with vendors to address product limitations, customization needs, and integration challenges.&nbsp;&nbsp;</li><li>Ensure compliance with internal standards and regulatory requirements during implementation.&nbsp;&nbsp;</li><li>Document technical specifications, deployment procedures, and support guides.&nbsp;</li></ul> Requirements&nbsp;&nbsp; <ul><li>Experienced in software development roles, with at least 2 years in a senior or lead capacity.&nbsp;&nbsp;</li><li>Proven eperience in banking or financial services, especially in compliance or payments.&nbsp;&nbsp;</li><li>Strong understanding of SDLC processes and experience in technical design and impact analysis.&nbsp;&nbsp;</li><li>Experience implementing and managing vendor products in enterprise environments.&nbsp;&nbsp;</li><li>Proficient in Unix/Linux shell scripting and SQL.&nbsp;&nbsp;</li><li>Hands-on experience with Java for defect resolution and enhancements.&nbsp;&nbsp;</li><li>Familiarity with payment technologies (SWIFT messaging, transaction flows) and AML systems&nbsp;&nbsp;</li><li>Experience with DevOps practices and CI/CD tools (Jenkins, Artifactory, SonarQube) will be an added&nbsp;</li><li>advantage&nbsp;&nbsp;</li><li>Degree in Computer Science, Engineering, or a related field.&nbsp;&nbsp;</li><li>Additional certifications in payment or compliance technology are advantageous&nbsp;&nbsp;</li></ul>

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Senior Executive – Data Analytics

RCSA & Internal Control Analyst

Structural Test Engineer

Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Technology Obsolescence - Task force - Data Specialist (VP1)

Specialist, Application Monitoring & Dashboard Analytics (VP2)

Lead, AI & Data Products (Technical)

Account Manager

Senior Team Lead

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207 external stakeholders Jobs found

Senior Executive – Data Analytics

RCSA & Internal Control Analyst

Structural Test Engineer

Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Technology Obsolescence - Task force - Data Specialist (VP1)

Specialist, Application Monitoring & Dashboard Analytics (VP2)

Lead, AI & Data Products (Technical)

Account Manager

Senior Team Lead

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