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Sr Azure Data Engineer

  • Sr Azure Data Engineer job type Posted on: Oct 14, 2026
  • Sr Azure Data Engineer experience level VeeRteq Solutions Inc
  • Sr Azure Data Engineer employment type Chicago, Illinois
  • Sr Azure Data Engineer employment type Onsite
  • Sr Azure Data Engineer salary CTC

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Job Title :

Sr Azure Data Engineer

Job Type :

Contract

Job Location :

Chicago Illinois United States

Remote :

No

Jobcon Logo Job Description :

Sr. Azure Data Engineer

Experience: - 10+ Years

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

Duration: - Long Term

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.

Jobcon Logo Position Details

Posted:

Oct 14, 2026

Reference Number:

4619-15867

Employment:

CTC

City:

Chicago

Job Origin:

CIEPAL_ORGANIC_FEED

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Sr. Azure Data Engineer

Experience: - 10+ Years

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

Duration: - Long Term

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.

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