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Senior Data Engineer (Databricks)

Paul May Associates

Job Title: Senior Data Engineer (Databricks)



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



Position Type: Full-Time, Direct Hire

OVERVIEW

Our Partner is casting a line for 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

COMPENSATION INFORMATION

The expected salary range for this position is $150,000-$164,000 per year, depending on experience and qualifications. This role also qualifies for comprehensive benefits such as health insurance, 401(k), and paid time off.

If applying for this role - Please take each key point and provide number of years experience and what you would rate yourself, 1 thru 10 (10 being expert) for each key point. Send your resume and notes on the role to expediate our recruiting services.

Vacancy posted more than 2 months ago

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