Sr Data Engineer (Data Bricks)

Job Title: Senior Data Engineer (Databricks)

Primary Location: Chicago, IL (Hybrid – 3 days onsite / 2 days remote)

Position Type: Full-Time, Direct Hire

Must Be Citizen or Green Card

OVERVIEW

A Senior Data Engineer. This is a full-time, direct hire role in Chicago, IL, working a hybrid schedule with a minimum of three days onsite per week. This role exists as part of a multi-year initiative to transform our client's Data & AI function, building a modern data platform that enables speed-to-insight and makes the organization truly data-driven.

You'll be one of the core builders of a brand-new Azure Databricks platform, designing and delivering the pipelines, transformations, and models that everything else runs on. The environment is greenfield: Databricks is stood up, but no production pipelines exist yet, so you'll help set the standards from day one. This is a hands-on senior individual contributor role, not a people management, architecture, AI/LLM, or BI/reporting role. The architecture is defined; your job is to build it well and raise the technical bar of a growing team (expanding to 25–30) that is largely BI-focused today.

The work carries strong executive sponsorship and enterprise-wide visibility, with the chance to influence engineering practices across the organization. The interview process includes a live technical assessment covering Python, SQL, and practical data pipeline logic.

WHAT YOU BRING TO THE ROLE. (IDEAL EXPERIENCE)

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field


• 6+ years of hands-on data engineering experience, with a track record of owning pipelines end to end: ingestion, validation, transformation, and governance


• Real, hands-on Databricks experience (Azure preferred; AWS or GCP acceptable), including Delta Lake, Unity Catalog, Databricks SQL, Spark clusters, and Workflows/Jobs


• Strong coding skills in Python, SQL, and Apache Spark that go well beyond basic scripting


• Proven experience designing and building scalable ETL/ELT pipelines, including reusable, metadata-driven pipelines


• Experience with object storage, lakehouse engines, orchestration tools, and streaming or CDC pipelines


• Solid data modeling, schema design, and performance tuning experience


• Working knowledge of Git-based workflows, CI/CD, test automation, and monitoring and alerting


• Strong troubleshooting skills and a solid grasp of engineering fundamentals: scalability, reliability, and maintainability


• The ability to clearly explain what you built, why it mattered, and how it solved a business or platform problem

Preferred Experience building or migrating a data platform from the ground up

• Infrastructure as Code (Terraform, Bicep, ARM) and Governance as Code experience


• Multi-cloud background with depth in Azure


• Legacy data warehousing and/or Hadoop experience


• Deep Databricks exposure beyond basic pipelines, such as enterprise-scale work and optimization


• A track record of mentoring and upskilling peers


• Agile delivery experience

WHAT YOU'LL DO. (SKILLS USED IN THIS POSITION)

• Lead the design and build of scalable data pipelines and models in Azure Databricks on a brand-new platform with no production code yet


• Own pipelines end to end, from ingesting source systems to transforming and modeling data to producing outputs for downstream analytics, BI, and AI/ML use cases


• Refactor and migrate multiple legacy data warehouses into the centralized Databricks lakehouse


• Work at the code level every day in Python, SQL, and Spark, building pipelines with Databricks Asset Bundles, Spark workflows, and API-driven jobs


• Establish engineering standards for CI/CD (GitHub/Azure DevOps), automated data testing, monitoring, and alerting


• Help shape and enforce standards for data modeling and governance


• Troubleshoot and optimize performance across the platform


• Mentor and coach junior engineers, conduct code reviews, and lead by example in design, coding, and testing practices


• Partner with Data Engineering, BI, AI, Finance, and product owners, and help translate technical work into business impact