Data Engineer building data integration pipelines for data lakes and warehouses. Collaborating with stakeholders to meet business requirements in a leading publishing company.
About the role
- Senior Data Engineer optimizing data pipelines and analytics for a SaaS company focusing on loyalty programs and online ordering. Building ETL processes and ensuring reliable data flow for insights.
Responsibilities
- You're the bridge between raw operational chaos and polished analytics.
- 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
- 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
Requirements
- 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
Benefits
- 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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