Senior Executive – Data Analytics

Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Cloud Engineering Manager

Technology Obsolescence - Task force - Data Specialist (VP1)

Account Manager

Supply Planning Leader

Customer Engineer

Supervisor Supply Chain

Tax Accountant

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>

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: <ul><li>Lead the engineering, operation, and continuous improvement of enterprise cloud platforms across Microsoft Azure (primary), AWS, and GCP, including landing zones, networking, platform services, and secure cloud foundations.</li><li>Build and maintain standardized delivery pathways, CI/CD pipelines, infrastructure-as-code (IaC) modules, GitOps practices, and environment automation to enable consistent, scalable, and compliant deployments.</li><li>Drive an automation-first engineering model, reducing manual intervention through policy-as-code, automated workflows, AI-assisted engineering, and agent-based execution of routine operational activities.</li><li>Develop and mature AIOps capabilities, including anomaly detection, intelligent alert correlation, automated remediation, and measurable reduction of operational toil.</li><li>Design and operate infrastructure supporting enterprise AI workloads, including GPU/accelerated compute, managed AI services, model serving and inference endpoints, vector and retrieval services, and secure AI landing zones.</li><li>Partner with Data &amp; AI teams to provide scalable, secure infrastructure for AI solutions while managing capacity, quotas, workload isolation, and AI infrastructure consumption and cost reporting.</li><li>Lead cloud reliability, observability, and resilience, establishing service level objectives (SLOs), error budgets, metrics, logging, tracing, recovery playbooks, and validated RTO/RPO requirements.</li><li>Implement cloud security, identity, and compliance guardrails through secure baselines, policy-as-code, workload identities, privileged access controls, and Microsoft Entra ID integration.&nbsp;</li><li>Maintain platform compliance with applicable data protection and industry standards, including GDPR, CCPA, PCI-DSS, and SOC 2, in partnership with Global Cybersecurity and other governance teams.</li><li>Execute FinOps and cloud optimization initiatives, including tagging and cost allocation, rightsizing, scheduling, storage optimization, reservations, savings plans, committed spend, forecasting, and consumption reporting.</li><li>Support the organizations cloud-first transformation, including modernization and consolidation of VMware workloads and rationalization of AWS and GCP environments around strategic business requirements.</li><li>Lead and develop a globally distributed cloud engineering team, establishing engineering standards, structured code and design reviews, operational discipline, continuous learning, and accountability for cloud providers and engineering partners.</li></ul> Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent professional experience.</li><li>10+ years of progressive cloud and infrastructure engineering experience, including at least 3 years leading engineering teams with accountability for production platform services.</li><li>Expert-level, hands-on experience with Microsoft Azure, with demonstrated experience building and operating environments across AWS and GCP.</li><li>Deep experience with platform engineering and infrastructure-as-code, including Terraform, Bicep, GitOps, CI/CD pipelines, landing zones, and automated provisioning.</li><li>Demonstrated experience implementing cloud automation and AI-enabled operations, including AIOps, AI-assisted engineering, or agent-based automation.</li><li>Hands-on experience supporting AI/ML infrastructure, including GPU/accelerated compute, managed AI services, model serving, or AI workload platforms.</li><li>Strong production experience with Kubernetes (AKS, EKS, or GKE), cloud security, identity, observability, and reliability practices.</li><li>Experience leading distributed engineering teams and supporting highly available, business-critical technology environments.</li></ul> Preferred Skills <ul><li>Professional certifications such as Azure Solutions Architect Expert, AWS Certified Solutions Architect – Professional, Google Professional Cloud Architect, CKA, Terraform Associate, or FinOps Certified Practitioner.</li><li>Experience with Microsoft Entra ID, workload identity, privileged access, Conditional Access, zero-trust principles, and policy-as-code.</li><li>Experience with observability and SRE practices, including Grafana, Prometheus, Azure Monitor, CloudWatch, SLOs, and error budgets.</li><li>Working knowledge of FinOps, cloud cost optimization, tagging strategies, reservations, savings plans, and consumption reporting.</li><li>Experience migrating and modernizing VMware and on-premises workloads into cloud environments.</li><li>Experience leading global teams across the Americas, EMEA, and APAC.</li><li>Experience within aviation, transportation, logistics, field operations, or other 24/7/365 operational environments.</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>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>

Role Description: <ul><li>Supply Planning Leader is accountable for end-to-end supply planning across an assigned product portfolio and multiple distribution centers.</li><li>The role ensures timely, cost-effective product availability while balancing customer service, inventory health, working capital, capacity, and logistics performance. This leader converts demand into feasible supply plans, manages risks and constraints, and drives cross-functional execution and continuous improvement in a global, matrix environment.</li></ul> Responsibilities: <ul><li>Develop and execute supply plans aligned with customer demand, inventory targets, business priorities, capacity, material availability, supplier constraints, and transportation lead times.</li><li>Ensure finished-goods availability and timely replenishment across distribution centers, regional warehouses, and source plants by driving MRP recommendations and monitoring plan adherence.</li><li>Lead weekly and monthly supply reviews and actively support S&amp;OP and S&amp;OE by providing supply status, reviewing demand outlook, recommending trade-offs, and driving approved actions.</li><li>Optimize safety stock, MRP policies, inventory deployment, stock coverage, turns, availability, and working capital while maintaining healthy inventory levels.</li><li>Manage phase-in and phase-out planning for the assigned portfolio.</li><li>Identify demand-supply gaps, capacity bottlenecks, material constraints, revenue risks, and service opportunities; lead root-cause analysis, recovery plans, prioritization, and allocation decisions.</li><li>Support customer-service targets, including Fill Rate, STR, OTIF, and PP Confirmation, by aligning commitments with realistic supply capabilities.</li><li>Partner with Demand Planning, Procurement, Manufacturing, Logistics, Customer Service, Product Management, and Sales on material availability, inventory strategy, supply risks, and executive reviews.</li><li>Prepare monthly and annual inventory and freight projections and improve sourcing and transportation economics, including ocean buying from source.</li></ul> Requirements: <ul><li>Bachelor’s degree in Supply Chain Management, Engineering, Operations, Business, or a related field.</li><li>10+ years of experience in supply planning, materials planning, inventory management, manufacturing, distribution, OEM, automotive, industrial, or aftermarket environments.</li><li>At least 4 years of team-leadership experience, with demonstrated stakeholder management, influencing, communication, and problem-solving capability.</li><li>Experience working effectively in fast-paced, global, matrix, and ambiguous environments.</li><li>Strong knowledge of supply and demand planning, forecasting, inventory optimization, capacity and constraint management, distribution networks, transportation, warehousing, and S&amp;OP/S&amp;OE.</li><li>Proficiency in SAP MRP and inventory planning, SAP IBP, and advanced Microsoft Excel; strong Microsoft PowerPoint and analytics capability.</li></ul>

Responsibilities: <ul><li>Install, maintain, and upgrade customer equipment&nbsp;</li><li>Apply basic diagnostic techniques to assess equipment and address technical issues, with assistance from Senior Field Service Engineers [Customer Engineers]&nbsp;</li><li>Collaborate with Senior Field Service Engineers [Customer Engineers] and/or the customer to understand roadmaps, process flows, inflection points, requirements, and&nbsp;</li><li>business challenges&nbsp;&nbsp;</li><li>Train and mentor junior Field Service Engineers [Customer Engineers]&nbsp;</li><li>Perform preventative and corrective maintenance on electrical, vacuum, mechanical, plasma, hydraulic, and gas systems&nbsp;</li><li>Coordinate and communicate directly with customers&nbsp;</li><li>Fulfill additional duties, as assigned.&nbsp;</li></ul> Requirements: <ul><li>Completion of a Diploma and/or Bachelor’s degree, military technical training, field service experience, or trade certification&nbsp;</li><li>4-7 years of work experience in semiconductor industry or other equipment support industry&nbsp;</li><li>Advanced mechanical aptitude with pneumatics, hydraulics, electronics, vacuum, and/or thermodynamics&nbsp;</li><li>Strong knowledge of hand tools and their appropriate usage, including digital multimeters&nbsp;</li><li>Effective written and verbal communication skills&nbsp;</li><li>Basic knowledge of Microsoft Excel, Word, and PowerPoint&nbsp;&nbsp;</li><li>Possession of a valid driver’s license and the ability to obtain a passport, if travel is required.&nbsp;</li></ul>

Role Description: <ul><li>Lead and supervise end-to-end supply chain planning for New Product Introduction (NPI) and New Product Development (NPD) projects at the Shirwal plant.</li><li>The role converts project requirements into executable material, production, capacity, inventory, packaging and logistics plans from early project gates through prototype, validation, pilot build, PPAP/PSW, SOP and ramp-up.</li><li>The position ensures launch readiness, timely risk escalation, disciplined SAP planning and structured handover to the regular MRP planning team after SOP.</li></ul> Responsibilities: <ul><li>Team Leadership &amp; Governance: Lead the NPI planning team, assign project ownership, review priorities and represent supply chain in plant and project launch reviews.</li><li>NPI Planning &amp; Launch Readiness: Own supply chain deliverables from early project gates through prototype, validation, pilot, PPAP, SOP and ramp-up, ensuring material and capacity readiness.</li><li>SAP, Master Data &amp; Material Planning: Ensure timely setup of parts, BOMs, routings, sourcing and MRP parameters. Convert project demand into executable material plans and manage shortages and MRP exceptions.</li><li>Supplier &amp; Cross-Functional Coordination: Coordinate with Procurement, Suppliers, Engineering, Quality, Operations, Logistics and Project Management to secure materials, tooling, packaging, capacity and shipment readiness.</li><li>Risk, Cost &amp; Change Management: Maintain launch risk visibility and control engineering-change, inventory, premium-freight, capacity and obsolescence exposure through timely recovery actions and escalation.</li><li>Performance Improvement &amp; Handover: Standardize NPI planning dashboards and routines, improve data quality and automation, and complete a controlled handover to the series MRP controller after SOP. KEY DELIVERABLES / SUCCESS MEASURES</li><li>On-time completion of NPI supply chain deliverables and gate commitments.&nbsp;</li><li>Material availability and build readiness for prototype, validation, pilot, PPAP and SOP events.</li><li>Accurate BOM, sourcing and MRP master-data readiness before planning execution.</li><li>Clear visibility of shortages, capacity constraints, inventory exposure, freight risk and recovery dates.</li><li>On-time PPAP/PSW support, SOP achievement and stable ramp-up without avoidable customer disruption.</li><li>Controlled inventory, premium freight and obsolescence exposure through early risk management.</li><li>Timely and complete handover from NPI planning to regular series planning after SOP.</li></ul> Requirements: Technical Skills <ul><li>SAP planning and procurement processes (MRP, stock/requirements analysis, material master, PR/PO and inventory visibility) - mandatory.</li><li>Advanced Microsoft Excel, including analytical models, PivotTables, lookups, dashboard preparation.</li><li>Power BI or an equivalent reporting and visualization tool.</li><li>Working knowledge of BOMs, routings, capacity planning, production scheduling, inventory planning, supplier lead times and logistics.</li><li>Good understanding of automotive NPI/NPD phases, PPAP/PSW readiness.</li><li>Bachelors degree, preferably in Engineering, Supply Chain, Operations or a related discipline.</li><li>MBA or equivalent postgraduate qualification is preferred.</li><li>Strong analytical, problem-solving and data-management capability.</li><li>Clear communication, stakeholder management and cross-functional partnership skills.</li><li>Working knowledge of automotive manufacturing, launch planning and project-gate governance.</li><li>3 to 7 years of relevant experience in supply chain, material planning, production planning or NPI/NPD planning within a manufacturing environment.</li><li>Experience managing material and capacity readiness for new product launches from prototype through SOP and ramp-up.</li><li>Hands-on experience with SAP MRP, planning master data, shortage management and supplier follow-up.</li><li>Experience coordinating across Project Management, Engineering, Quality, Operations, Procurement and Logistics.</li><li>People leadership or team-coordination experience, with evidence of disciplined follow-up and escalation.</li></ul>

Responsibilities: <ul><li>Sales and use tax journal posting and prepare the check request for tax payments.</li><li>Resale and exemption certificate management</li><li>Business license registration and renewal</li><li>Resolving customer related tax questions and tax exemption issues</li><li>Calculation and submission of payments to tax authorities</li><li>Reconciling tax payments with accruals and record journal entries to adjust, if needed</li><li>Creation of custom reports as required by company US tax teams using SAP macros and Power Query External Use</li><li>Preparation of tax account reconciliation and various other data pulls from SAP and Vertex O series for tax compliance requirements.</li><li>Works independently; receives guidance when needed.</li></ul> Requirements: <ul><li>Bachelor’s degree in economics, Statistics, Accounting, or other related field</li><li>3 to 5 years of experience from Big 4 Accounting or Large MNC Corporate Tax Department (Preferably In house)</li><li>Experience in preparing and reviewing Sales Tax and Use Tax returns</li><li>Experience demonstrating problem solving skills and the ability to prioritize and manage multiple tasks.</li><li>Advanced proficiency with Microsoft Excel (macros, advanced formulas including “v-lookup” and “index match”)</li><li>Experience in tax exemption certificate management.</li><li>Experience in business license registration and renewal.</li><li>Experience in tax accounts reconciliation.</li><li>Experience with Vertex O Series Indirect Tax Determination for North America Region</li></ul>

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115 microsoft power bi Jobs found

Senior Executive – Data Analytics

Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Cloud Engineering Manager

Technology Obsolescence - Task force - Data Specialist (VP1)

Account Manager

Supply Planning Leader

Customer Engineer

Supervisor Supply Chain

Tax Accountant

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Senior Executive – Data Analytics

Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Cloud Engineering Manager

Technology Obsolescence - Task force - Data Specialist (VP1)

Account Manager

Supply Planning Leader

Customer Engineer

Supervisor Supply Chain

Tax Accountant

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