Senior Data Engineer — AI/ML Pipelines on Azure

Tiger Analytics Inc.; Chicago (IL); On-site; USD 100,000 - 150,000; Full time

Job summary

Tiger Analytics is seeking an experienced Data Engineer in Chicago to design, build, and maintain scalable ETL/ELT pipelines on the Azure data stack. You will work with data scientists and BI teams to support analytics, ML/Generative AI initiatives, and data infrastructure.

This role emphasizes governance, security, and efficient cloud data processing. You'll collaborate across teams to optimize performance, enable reporting via dimensional data marts, and implement end-to-end data lineage with

Qualifications

• Experience designing scalable ETL/ELT pipelines on Azure data services.
• Strong data modeling for data lakes and marts (Star/Snowflake).
• Proficiency with PySpark, SQL/NoSQL, and streaming workloads.
• Experience implementing data governance, lineage, and data quality controls.
• Knowledge of security controls (RBAC, key vaults, encryption) for data pipelines.

Responsibilities

• Design, build, and maintain scalable data pipelines on Azure cloud.
• Collaborate with data scientists and analysts to support analytics and AI initiatives.
• Model dimensional data marts to enable reporting and BI.
• Implement data governance, quality checks, and lineage tracking.
• Automate deployments and CI/CD for data infrastructure.

Skills

Data engineering

ETL/ELT design

PySpark

Data modeling

Streaming data processing

Data governance

Security best practices

CI/CD

Tools

Azure Data Factory

Azure Synapse

Azure Databricks

ADLS Gen2

Delta Lake

Microsoft Purview

Azure DevOps

GitHub Actions

Job description

Tiger Analytics is seeking an experienced Data Engineer in Chicago to design, build, and maintain scalable ETL/ELT pipelines on the Azure data stack. You will work with data scientists and BI teams to support analytics, ML/Generative AI initiatives, and data infrastructure.

This role emphasizes governance, security, and efficient cloud data processing. You'll collaborate across teams to optimize performance, enable reporting via dimensional data marts, and implement end-to-end data lineage with