Sr. Azure Data Engineer

Roles and Responsibilities: -

Develop and manage data solutions based on Lakehouse Architecture, Delta Lake, and Medallion (Bronze, Silver, Gold) frameworks.

Create and maintain dimensional and normalized data models to support analytics and reporting needs. Implement data quality checks, validation frameworks, monitoring, and reconciliation processes.

Optimize data processing jobs for performance, scalability, reliability, and cost efficiency. Collaborate with Data Architects, Business Analysts, BI Developers, and stakeholders to understand business requirements and translate them into technical solutions. Participate in code reviews, testing, deployment, and production support activities.

Develop reusable frameworks and best practices for data engineering and platform development. Troubleshoot and resolve performance bottlenecks, data issues, and production incidents.

Ensure compliance with data governance, security, and regulatory requirements

Experience: -

10+ Years

Location: -

Chicago, IL (Hybrid 3 days' Work from Office)

Duration: -

C2H role

Educational Qualifications: -

Engineering Degree BE/ME/BTech/MTech/BSc/MSc.

Technical certification in multiple technologies is desirable.

Skills: -

Mandatory skills

10+ years of Data Engineering experience with strong focus on modern cloud data platforms. Hands-on experience with Databricks, PySpark, SQL, and Python.

Strong understanding of ETL/ELT design patterns, data integration, and data warehousing concepts. Experience with relational databases, data modeling, partitioning, indexing, and query optimization.

Expertise in building and maintaining large-scale data pipelines and batch processing solutions. Experience working with cloud platforms such as Azure, AWS, or GCP. Strong problem-solving, debugging, and analytical skills. Proven experience architecting and delivering systems using agentic IDEs

Ability to: Define architectural intent that agents can follow Break features into agent executable tasks Govern AI autonomy (guardrails, permissions, reviews) Integrate agentic workflows into CI/CD pipelines

Experience supervising AI agents across: Multi service systems Legacy modernization Large codebases / monorepos

Strong understanding of: Security implications of autonomous code execution Compliance, auditability, and traceability AI assisted SDLC operating models

Core Responsibility: Guide effective use of agentic IDEs for complex, multi-module or cross-service changes Establish review practices and quality checks for AI-generated code Mentor team members on balancing autonomy, correctness, and maintainability in AI-assisted development

Design system architectures that support AI-augmented and agentic development workflows Define guardrails, standards, and governance for the use of autonomous coding agents Evaluate impact of agentic IDEs on SDLC, CI/CD pipelines, security posture, and technical debt.

We are currently looking for candidates who are authorized to work in the United States without requiring current or future visa sponsorship.