Description

• Use GitHub Copilot as a hands-on engineering environment to analyze existing code, design and implement production-quality changes, generate and maintain tests and documentation, debug failures, review proposed changes, and verify outcomes with executable evidence. • Design, build, test, and operate AI agents that plan and execute multi-step workflows using LLM reasoning, structured prompts, context and memory, retrieval, APIs, data tools, and human approval gates to enhance data engineering, reporting, testing, and operational processes. • Develop tool-enabled agents and Model Context Protocol (MCP) integrations that securely connect AI assistants to enterprise APIs and platforms, including BI/reporting services, data products, work-management systems, and operational knowledge sources. • Implement browser and UI automation agents for authenticated enterprise workflows, evidence capture, regression testing, test generation and healing, and operational workflows, using tools such as Playwright and browser developer protocols. • Define agent evaluation, observability, and safety controls, including grounded-response checks, deterministic tool contracts, structured outputs, least-privilege credential handling, approval checkpoints, test datasets, execution traces, failure recovery, and measurable quality and productivity outcomes. • Develop and implement data mesh and data fabric architectures to enable decentralized data management and access. • Build data and BI development agents that generate and validate SQL, DAX, semantic models, reports, data-product specifications, quality tests, and deployment artifacts while preserving governance, auditability, and human review. • Develop user personas and business personas in alignment with data requirements and deliver solutions that meet business needs. • Work with business users to translate functional specifications into technical designs for implementation and deployment • Work with cross functional team members to develop prototype, produce design artifacts, develop components, perform and support SIT and UAT testing, triaging and bug fixing. • Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs • Ensure high quality and optimum performance of data systems to meet business expectations." "• 2+ years of hands-on experience using GitHub Copilot or similar AI-assisted engineering tools across the software development lifecycle, including requirements analysis, coding, refactoring, testing, debugging, documentation, code review, and verification. • 2+ years of hands-on experience designing and building Agentic AI solutions using prompt and context engineering, LLMs, RAG, structured tool/function calling, APIs, memory or state management, human-in-the-loop controls, and AI governance principles. • Hands-on programming experience in Python, Java, TypeScripts and SQL, with the ability to design agent tools, API clients, MCP servers, command-line workflows, typed data contracts, and automated tests for enterprise use cases. • Experience integrating agents with enterprise authentication, APIs, databases, knowledge repositories, BI platforms, and browser automation while protecting credentials, sensitive data, and audit trails. • Demonstrated ability to evaluate agent quality through unit, integration, behavioral, and end-to-end tests; diagnose hallucinations and tool failures; instrument execution; and improve prompts, retrieval, context, and workflows using evidence. Broader candidate background preferences - • 5+ years of experience with data virtualization, data mesh, data fabric, and federated querying platform such as Denodo, Starburst or OSS platforms is highly desirable. • 5+ Years of experience working as a Report Visualization Engineer with Power BI, Tableau, or any similar Reporting Platforms with End-to-End delivery. • 3+ Year of experience with implementation of Data Modelling, Data Governance and RLS. • 3+ Years of experience with Enterprise Deployment Strategies and migration of legacy platform reports to modern reporting platforms. • Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes or modern data platforms like Snowflake. • Solid understanding of data modeling, database design, and ETL principles. • Familiarity with data governance, data security, and compliance practices in cloud environments. • Strong problem-solving skills and the ability to optimize and fine-tune data pipelines and Spark jobs for performance. • Tableau/Power BI / Snowflake / Starburst certifications on Data related specailities are a plus. • Power Platform experience (Power Apps, Power Automate) will be a plus

Key Skills

Education

Bachelor's degree