Role overview

Senior Data Engineer (Analytics Focus)

Requirements and responsibilities

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Most of your time:

  • Building ETL/ELT pipelines that ingest, transform, and serve data at scale
  • Designing warehouse schemas (star schemas, fact tables, the whole dimensional modeling thing)
  • Creating pre-aggregated datasets so dashboards load fast and analysts stay happy
  • Making sure data flows reliably from source systems → transformations → analytics layer

Some of your time:

  • Partnering with analytics team to understand what data they actually need
  • Optimizing the infrastructure so it doesn't cost a fortune or fall over
  • Building data quality checks because garbage in = garbage out

You should have

  • 5+ years in data engineering (not just DBA work — actual pipeline and warehouse experience)
  • SQL fluency — complex transformations, window functions, performance tuning
  • ETL/ELT chops — you've built pipelines that process serious volume
  • Data modeling experience — star schemas, SCDs, fact vs dimension tables
  • Python or C# — for the stuff SQL can't do
  • Cloud experience — Azure preferred (Data Factory, Azure SQL, Functions)

Bonus points for

  • SaaS or multi-tenant analytics experience
  • Restaurant/retail/loyalty domain knowledge
  • Real-time or near-real-time data pipeline experience
  • Having opinions about dbt, Airflow, or modern data stack tools

What We Offer

  • Generous time off plan
  • Fully remote work & support to assist with making your remote office space as comfortable as possible!
  • Continuous virtual coaching and support
  • Comprehensive health benefits
  • Subsidized gym membership
  • Performance recognition
  • Professional development program
  • Growth opportunities (we really mean it!)
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Browse stack
FocusData EngineeringRole area
Seniority signalSeniorCandidate level
StackAzure, PostgreSQL, PythonPrimary skills
Location1 accepted countryEligibility

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