Security Engineer – Data Security Engineering (VP1)

Consultant, Data Analytics & Reporting-Food

Forward Deployed AI Strategist

SAP Lead

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Sr. Application Developer

Principal Platform Engineering – Digital Integration

SAP Basis Engineer

Responsibilities: <ul><li>Create dashboards, alerts, reports in Splunk.&nbsp;</li><li>Maintain and enhance existing reports for business.</li><li>Develop the necessary test cases and perform testing.</li><li>Implement and operationalize the use cases.</li><li>Create and maintain documentation in accordance to Bank standards.&nbsp;</li><li>Ensure appropriate standards and procedures are adhered to during the development process to support quality deliverables.</li><li>Troubleshoot, debug and provide production system support for Data Security Engineering services.</li><li>Coordinate with internal teams and vendors to resolve system issues.</li><li>Execute tasks related to project / change request / maintenance request.</li></ul> Requirements: <ul><li>Diploma/Degree in engineering/Computer Science / IT/Cyber Security from a recognized education institution.</li><li>Data Security product certifications will be favorable although not mandatory&nbsp;</li><li>Overall, 6 years of work experience in information technology and at least 2 years in Cyber Security.</li><li>Working experience in integrating solution with Splunk and developing Splunk contents (alerts, reports and dashboards).</li><li>At least 3 years of relevant experience in managing and deploying Data Security Solutions</li><li>Data Security or Splunk product certifications will be favorable although not mandatory.</li><li>Knowledgeable with the variety of Data Security technologies and familiar with the industry trends and best practices.</li><li>Analytical problem solver and good at troubleshooting technical issues</li><li>Hands-on experience with Windows, Unix or Linux and endpoint management tools (e.g. SCCM, JAMF).</li><li>Proficiency in network technologies, scripting and automation (e.g. PowerShell scripts, Python).</li><li>Advanced level of proficiency in Microsoft Office products.</li></ul>

Responsibilities: <ul><li>Data Analysis: Collects, transforms, and analyzes data from multiple sources to identify trends, patterns, anomalies, and actionable insights that support reporting, performance tracking, and decision making.</li><li>Reporting &amp; Visualization: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.</li><li>Data Modeling &amp; Automation: Supports data models, reporting logic, and workflow automation, while identifying and implementing opportunities to improve data collection and reporting processes using standard data management and reporting practices.</li><li>Advanced Analytics Awareness: Familiarity with predictive analytics, AI/ML, and data science concepts to support evolving analytics solutions.</li><li>Data Quality &amp; Requirement Support: Validates data, supports reporting requirements, and helps ensure the accuracy and consistency of analytics solutions.</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field such as Data Science, Statistics, Computer Science, Business Analytics, or a related discipline, or equivalent practical experience.&nbsp;</li><li>Minimum of 3-4 years of relevant work experience in data analytics, reporting, or business intelligence roles.</li><li>Strong skills in analyzing data and translating reporting needs into effective analytics solutions and insights.</li><li>Very strong skills in Power BI and data visualization.</li><li>Proficiency in SQL, Excel, Power Query, and related tools such as VBA or Python for analysis, modelling, and visualization.</li><li>Working knowledge of data warehousing, data lakes, and cloud data platforms such as Snowflake or AWS.</li><li>Experience automating workflows and building low-code solutions using Power Platform tools such as Power Automate and Power Apps.</li><li>Familiarity with (predictive) analytics, AI/ML and data science.</li><li>Business understanding and financial acumen to interpret data and generate practical insights.</li><li>Comfortable working in agile ways of working, managing multiple priorities, and contributing effectively both independently and in a team environment.</li></ul>

Role Description: <ul><li>The Strategy team is looking for a hands-on AI-enabled strategy and market intelligence professional to materially accelerate the way we conduct deep research, market intelligence, analytical modeling, and GTM analysis by applying high impact AI workflows and translating them into sharper strategic decisions.</li><li>The individual will partner with business, product, commercial, and tech teams to translate ambiguous questions into actionable insights, while developing and scaling AI-enabled solutions that improve strategic decision-making and drive measurable business impact.&nbsp;</li><li>The individual is expected to work in close partnership with our client IT team, to leverage existing AI &amp; data capabilities on Databricks &amp; AWS (where applicable) while developing solutions.</li></ul> Responsibilities: Strategic problem solving and driving cross-functional execution&nbsp; <ul><li>Translate AI-assisted analyses into practical executive decisions by applying strong business judgment, rigorous validation protocols, and a sharp “so-what” orientation</li><li>Collaborate with and influence senior stakeholders across strategy, sales, technology teams, and P&amp;L owners</li><li>Good first-principles and problem-solving capabilities with the ability to build and test strategic hypotheses Identifying meaningful opportunities to leverage AI and deploying scaled AI solutions at pace</li></ul> Identify, assess, and prioritize high-value AI and automation opportunities by translating business challenges into scalable, practical solutions&nbsp; <ul><li>Design proprietary AI-enabled workflows, agents, and accelerators for recurring strategy activities (competitor monitoring, earnings call tracking, tariff and regulatory intelligence, voice-of-customer mining etc.)</li><li>Build reusable templates, workflows, and modules to drive adoption and embed AI capabilities into strategy processes</li></ul> Executing rapid AI-augmented research and competitive intelligence&nbsp; <ul><li>Lead AI-augmented research using tools like Claude, OpenAI, Perplexity, AlphaSense, CapIQ etc. to deliver source-triangulated competitive and industry insights</li><li>Synthesize structured datasets (S&amp;P Capital IQ, Bloomberg, IDC, Gartner) and unstructured sources (10-Ks, analyst reports, expert interviews) – to generate and validate AI-assisted outputs</li></ul> Support strategy team in day-to-day execution by leveraging AI-led tools <ul><li>Lead AI-enabled market sizing, opportunity mapping, and TAM/SAM/PAM modelling</li><li>Accelerate financial modelling – scenario and sensitivity analyses, valuation, NPV/IRR, segment P&amp;Ls, pricing</li><li>Support M&amp;A pipeline by AI-screening targets and generating investment theses</li></ul> AI enablement, coaching and continuous innovation <ul><li>Coach strategy team members on prompting techniques, research workflows, and AI-fluent execution</li><li>Scale AI adoption across Corporate Strategy through hands-on mentorship of beginner users</li><li>Stay current on agentic stacks, multimodal models, and deep research agents</li></ul> Requirements: Skillset and capabilities AI fluency and hands-on deployment orientation&nbsp; <ul><li>Working knowledge of GenAI patterns – LLM capabilities/limitations, prompt design, etc.</li><li>Proven ability to convert business problems into reusable AI workflows, tools, or accelerators</li><li>Builder mindset with experience prototyping AI solutions using frontier tools &amp; low-code platforms</li></ul> Analytics, modelling, and research excellence <ul><li>Strong modelling skills across TAM/SAM/PAM, scenarios, sensitivities, NPV/IRR, valuation etc.</li><li>Ability to synthesize structured datasets with unstructured sources</li><li>Research discipline – source triangulation and rigorous validation of AI outputs</li></ul> Strategic problem solving, communication, executive presence, and influence&nbsp; <ul><li>Sharp "so-what" orientation to translate AI outputs into practical executive decisions</li><li>Crisp written and verbal communication, with ability to frame board-ready narratives</li><li>Skill in explaining AI workflows and implications to both technical and non-technical audiences</li><li>Stakeholder management across strategy, commercial, data, and technology teams</li></ul> Ownership, and execution <ul><li>Independently own workstreams end-to-end – from framing through deployment</li><li>High bar for quality; never publishes unchecked AI outputs or unvalidated analysis</li></ul> Coaching and capability building&nbsp; <ul><li>Patience and ability to coach colleagues on prompting, research workflows, and source validation</li><li>Track record of building reusable playbooks – templates and training modules that scale adoption</li></ul> Passion, curiosity, and learning agility <ul><li>Deep passion for AI, tech, and industrial innovation, with curiosity to stay current on frontier tools</li><li>Entrepreneurial ownership mindset and drive to build a new AI-enabled strategy capability</li></ul> Qualifications:&nbsp; <ul><li>BE / B-Tech in Computer Science Engineering, Data Science or a related analytical field required; MBA, MS, M-Tech or equivalent advanced degree strongly preferred.</li><li>3–4+ years of experience in AI transformation, analytics, or AI-enabled business building. Prior Forward Deployed Engineer / Solutions Architect / Senior Data Scientist background preferred.</li><li>Experience in a top-tier strategy consulting firm, AI-native consulting team, analytics firm or corporate / product strategy team role strongly preferred.</li><li>Demonstrated experience building or deploying 0–1 AI solutions (not just experimenting), GenAI, analytics, automation, or workflow solutions in a business environment required.</li><li>Proficiency in Excel and PowerPoint required; Python or equivalent scripting capability strongly preferred. Experience with DevOps, CI/CD pipelines, and infra as code (e.g., Jenkins, Docker, Kubernetes) required.</li><li>Proficient in implementing AI platforms like AWS Bedrock, LangGraph, Crew AI, Glean etc.</li><li>Knowledge of enterprise data environments (esp. SAP, Databricks) or cloud platforms (esp. AWS) is a plus. Experience integrating AI systems with enterprise data platforms required.</li><li>Experience with LLM-powered solutions, RAG systems, agentic workflows, AI research tools, or AI-enabled knowledge manage</li></ul>

Responsibilities: <ul><li>Lead and manage the SAP support team responsible for supporting global manufacturing operations.</li><li>Act as the key interface between business stakeholders, SAP functional teams, and external partners.</li><li>Drive post-go-live stabilization, continuous improvement, and process optimization initiatives across the SAP landscape.</li><li>Provide cross-functional oversight across SAP FICO, MM, PP, SD, and Security modules.</li><li>Ensure effective issue resolution and support delivery for business-critical processes.</li><li>Partner with regional and global stakeholders to understand business requirements and translate them into SAP solutions.</li><li>Support enhancement initiatives and contribute to process standardization across multiple sites.</li><li>Guide and mentor SAP Business Analysts while fostering collaboration and knowledge sharing within the team.</li><li>Monitor support performance and ensure service levels are maintained.</li><li>Contribute to the long-term SAP roadmap and help shape the SAP operating model.</li></ul> Requirements: <ul><li>Bachelors degree in Information Technology, Computer Science, Business Administration, or a related discipline.</li><li>Strong functional expertise in SAP, with preference for candidates possessing a FICO background.</li><li>Broad understanding of end-to-end business processes and cross-functional integration across MM, PP, SD, and Security.</li><li>Experience supporting SAP S/4HANA environments.</li><li>Hands-on experience in SAP implementation, rollout, or post-go-live support projects.</li><li>Strong understanding of manufacturing business processes and experience supporting manufacturing environments.</li><li>Ability to perform functional analysis, configuration, testing, and issue resolution.</li><li>Proven experience leading, mentoring, or managing SAP teams.</li><li>Strong stakeholder management and business partnering capabilities.</li><li>Experience working in regional or global environments with multiple business units or sites.</li><li>Excellent communication, analytical, and problem-solving skills.</li><li>Ability to operate effectively in a fast-paced and collaborative environment.</li><li>Preferred Qualifications</li><li>Experience in SAP S/4HANA Public Cloud environments.</li><li>Exposure to manufacturing system integrations and third-party applications.</li><li>Experience in establishing or supporting SAP Centres of Excellence or shared service environments.</li><li>SAP certification(s) would be advantageous.</li><li>Experience supporting global template environments and process standardization initiatives.</li></ul>

Responsibilities: Design &amp; Build/Development &amp; Support <ul><li>Develop multi-agent workflow automation patterns using Agentic AI</li><li>Process redesign and mapping to agentic workflow patterns</li><li>Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).</li><li>Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents</li><li>Profile inference latency, GPU/CPU utilization, and memory</li><li>Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions</li><li>Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents</li><li>Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.</li></ul> Operational Excellence&nbsp;<ul><li>Own on-call runbooks, SLOs, and incident reviews; embed observability</li><li>Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.&nbsp;</li></ul> Collaboration &amp; Leadership <ul><li>Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.</li><li>Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.&nbsp;</li><li>Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.&nbsp;</li></ul> Capability &amp; Technology Stack Exposure <ul><li>Experience with digital technologies in the commercial &amp; sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)&nbsp;</li></ul> Requirements: <ul><li>Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.&nbsp;</li><li>Typically reflects 4 years or more with 3+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.&nbsp;</li></ul>

Responsibilities: Design &amp; Build/Development &amp; Support <ul><li>Develop multi-agent workflow automation patterns using Agentic AI</li><li>Process redesign and mapping to agentic workflow patterns</li><li>Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).</li><li>Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents</li><li>Profile inference latency, GPU/CPU utilization, and memory</li><li>Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions</li><li>Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents</li><li>Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.</li></ul> Operational Excellence&nbsp;<ul><li>Own on-call runbooks, SLOs, and incident reviews; embed observability</li><li>Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.&nbsp;</li></ul> Collaboration &amp; Leadership <ul><li>Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.</li><li>Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.&nbsp;</li><li>Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.&nbsp;</li></ul> Capability &amp; Technology Stack Exposure <ul><li>Experience with digital technologies in the commercial &amp; sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)&nbsp;</li></ul> Requirements: <ul><li>Minimum requirement of 2 years of building production software or data platforms.&nbsp;</li><li>Typically reflects 3 years or more with 2+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.&nbsp;</li></ul>

Responsibilities: Strategic Leadership: <ul><li>Set the vision and direction for data and AI architecture for project and client.</li><li>Influence enterprise data and AI strategies, driving adoption of best practices in data, ML, and AI architecture.</li><li>Mentor and develop junior architects and engineers, fostering a culture of technical excellence and innovation.</li></ul> Architectural Excellence: <ul><li>Architect and design enterprise-scale data platforms and ML/AI solutions for scalability, reliability, and performance.</li><li>Define and enforce data and ML architecture standards, patterns, and governance frameworks for data pipelines, ML workflows, and analytics platforms.</li><li>Lead solution design for integrating data from diverse sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services.</li></ul> AI &amp; ML Leadership: <ul><li>Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems.</li><li>Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models.</li><li>Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent data products.</li><li>Provide Ethical AI leadership to ensure intelligent solutions are implemented when required and in safe methods.</li></ul> Technical Leadership: <ul><li>Oversee data modelling (e.g. medallion architecture), data governance, and quality frameworks. Implementing technical reviews and driving high standards.</li><li>Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform.</li><li>Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps).</li></ul> Stakeholder Engagement: <ul><li>Engage with senior stakeholders to translate complex business requirements into technical solutions and strategic roadmaps.</li><li>Ensure all solutions meet security, compliance, and performance standards, and align with enterprise architecture principles.</li></ul> Innovation &amp; Emerging Technologies: <ul><li>Apply modern data and AI architecture patterns (Cloud Native, Steaming/batch ingestion, Agentic AI Design) and leverage platforms such as AI/ML, Big Data, and Data Lakehouse.</li></ul> Requirements: <ul><li>Minimum 8 years’ experience client facing roles specializing in Data and Architecture roles.</li><li>Experience in both Agile and Waterfall project environments.</li><li>Strong stakeholder management and communication skills.</li><li>Security and compliance awareness.</li><li>Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer).</li><li>Experience mentoring or managing technical teams.</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain web applications using Java, Spring Boot, React, Redux, and PostgreSQL</li><li>Implement and manage APIs and microservices architecture</li><li>Ensure the performance, quality, and responsiveness of applications</li><li>Identify and correct bottlenecks and fix bugs</li><li>Partner with business stakeholders and operations team to identify and manage KPIs</li><li>Evaluate the performance of processes, services, and outcomes and drive performance improvement</li><li>Independently solve complex issues, lead a team of junior and mid-level developers</li><li>Other duties as assigned</li></ul> Requirements: <ul><li>Bachelor’s degree in computer science, Information Technology, or related field. Minimum of 12-15 years offull stack development related work experience</li><li>Strong oral and written communication skills</li><li>Expert in Java, Spring Boot, React, Redux, and PostgreSQL</li><li>Strong analytical skills with the ability to collect, organize, and analyze data</li><li>Attention to detail and accuracy is critical</li><li>Working knowledge of cloud platforms (e.g., AWS, Azure)</li><li>Adept at presenting findings in MS PowerPoint and MS Word</li></ul>

Responsibilities: <ul><li>Technical Leadership &amp; Strategy: Create long-term Integration Strategy and Roadmap, Define and implement Integration patterns &amp; standards</li><li>Technology Evaluation: Research, evaluate, and adopt emerging technologies, tools, and industry trends to enhance integration capabilities</li><li>Solution Architecture: Design scalable and reusable middleware components, including API gateways, message brokers, iPaas and application servers</li><li>Infrastructure Management: Deploy, manage and monitor integration solutions to ensure high availability, optimal performance and minimal downtime</li><li>Governance &amp; Standards: Establish and enforce best practices, security measures, and documentation standards for middleware platforms</li><li>Collaboration &amp; Leadership: Ability to work across teams, mentor engineers, and communicate technical strategies to stakeholders.</li><li>Experience: Substantial experience in multiple middleware technologies for architecture design, software development and system administration in both cloud-native and hybrid environments</li><li>Systems Thinking: Ability to evaluate, design and maintain future ready, secure, scalable digital integration solutions.</li></ul> Requirements: <ul><li>Minimum requirement of 8 years of relevant work experience. Typically reflects 12 years or more of relevant experience.</li><li>Technical Expertise: Strong proficiency with middleware technologies such as</li><li>Integration Platforms: Boomi, SAP BTP, MuleSoft</li><li>API Gateways: Kong, Layer7, Apigee</li><li>B2B/EDI: Open Text, Boomi, IBM Sterling</li><li>Messaging Queue: Kafka, Solace, Pulsar</li><li>Web/App Servers: WebLogic, WebSphere, Tomcat</li><li>Technical Services: Jira, GitHub, Azure DevOps, Datadog, AppDynamics</li></ul>

Responsibilities: <ul><li>Designs, builds, and supports SAP platform solutions by applying sound engineering practices to ensure system stability, performance, and scalability.</li><li>Utilizes enterprise tools and methodologies to automate system deployments, transport, and administrative activities, enabling reliable and repeatable releases.</li><li>Collaborate with cross‑functional partners to translate moderately complex business and technical requirements into effective SAP Basis solutions.</li><li>Performs system validation, technical testing, monitoring, and troubleshooting to maintain the quality and availability of SAP systems.</li><li>Contributes to continuous improvement initiatives by identifying opportunities to enhance SAP Basis processes, automation, and operational efficiency.</li><li>Creates and maintains clear technical documentation for SAP landscapes, configurations, and operational procedures.</li><li>Provides technical support for moderately complex SAP Basis issues, ensuring timely resolution and minimal impact to business operations.</li><li>Drives automation and quality through the use of enterprise testing and deployment tools, including Tosca for test automation and qTest for test management, execution, and traceability.</li><li>Develops, executes, and maintains manual and automated test assets for SAP systems, ensuring end‑to‑end coverage across SIT, UAT, regression, and integration testing cycles.</li><li>Performs system validation, monitoring, defect analysis, and troubleshooting in partnership with development, security, and infrastructure teams to ensure reliability and performance.</li></ul> Requirements: <ul><li>Minimum requirement of 5 years of relevant work experience with SAP Basis.&nbsp;</li><li>Demonstrated expertise in SAP Basis engineering, with strong knowledge of SAP system architecture, technical landscape design, system administration, upgrades, transport, performance monitoring, and operational support across multiple SAP environments.</li><li>Experience managing and supporting SAP technical operations, including system availability, batch processing, interfaces, background jobs, monitoring, troubleshooting, and incident resolution in alignment with enterprise service expectations.</li><li>Proven ability to support SAP Fiori and UI technical components from a Basis perspective, including configuration, activation, performance support, and coordination with security and application teams.</li><li>Experience leveraging scripting and technical tools (such as SQL and automation utilities) to improve operational efficiency, support system analysis, and standardize SAP Basis activities.</li><li>Working knowledge of cloud‑hosted and hybrid SAP landscapes, including experience supporting SAP systems on platforms such as Microsoft Azure, AWS, or Google Cloud, with an understanding of infrastructure, connectivity, and platform operations.</li></ul>

Skills

Industry

Location

Jobtitle

44 azure cloud Jobs found

Security Engineer – Data Security Engineering (VP1)

Consultant, Data Analytics & Reporting-Food

Forward Deployed AI Strategist

SAP Lead

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Sr. Application Developer

Principal Platform Engineering – Digital Integration

SAP Basis Engineer

WhiteCrow
WhiteCrow is on a mission to connect companies with the best talent across the globe.

EMPLOYER

TALENT

COMPANY

Contact Us

JOBS BY SKILLS

JOBS BY FUNCTION

JOBS BY INDUSTRY

JOBS BY LOCATIONS

MODEL JOBS

JOBS BY CITY

Skills

Industry

Location

Jobtitle

44 azure cloud Jobs found

Security Engineer – Data Security Engineering (VP1)

Consultant, Data Analytics & Reporting-Food

Forward Deployed AI Strategist

SAP Lead

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Sr. Application Developer

Principal Platform Engineering – Digital Integration

SAP Basis Engineer

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

EMPLOYER

TALENT

COMPANY

Contact Us

JOBS BY SKILLS

JOBS BY FUNCTION

JOBS BY INDUSTRY

JOBS BY LOCATIONS

MODEL JOBS

JOBS BY CITY

WhiteCrow
WhiteCrow is on a mission to connect companies with the best talent across the globe.