Description

Key Responsibilities

 Pipeline Development  Design| implement| and optimize scalable ETL/ELT pipelines using Databricks (PySpark| SQL| Delta Lake) to ingest structured and semi structured data from multiple sources (APIs| databases| streaming). 

Data Warehousing  Build and maintain cloud data warehouse solutions (Snowflake / Azure Synapse)  design star schemas| fact/dimension tables| and aggregate tables for high performance reporting.

 Data Modeling  Create logical and physical data models for operational and analytical use cases; implement SCD Type 2| slowly changing dimensions| and data vault methodologies where appropriate. Performance Tuning  Optimize Spark jobs| SQL queries| and data partitioning strategies to handle petabyte scale data with low latency.

 Governance & Quality  Implement data quality checks| monitoring| and lineage using tools like Great Expectations or custom frameworks; enforce data governance policies (GDPR/CCPA). Collaboration  Partner with data analysts| product managers| and engineers to translate business requirements into technical data solutions.

 CI/CD & Automation  Automate deployment of data pipelines using Azure DevOps or GitHub Actions; maintain infrastructure as code (Terraform) for data resources.

Essential Skills: 

We are seeking a skilled Data Engineer to join our growing data team in Chicago.

 In this role| you will design| build| and maintain robust data pipelines that power analytics| reporting| and machine learning initiatives.

  You will work hands on with Databricks on Azure| modern data warehousing platforms| and advanced data modeling techniques.

 This is a high impact position where you will own the end to end data lifecycle  from ingestion to serving  while collaborating closely with data scientists| analysts| and business stakeholders

Key Skills

Education

Bachelor's degree