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Tech Stack
Tools & technologiesAirflowApacheBigQueryCloudGoogle Cloud PlatformKubernetesPythonSQL
About the role
Key responsibilities & impact- Collaborate with stakeholders to decompose ambiguous problems into tested data solutions.
- Own our medallion architecture (bronze → silver → gold), ensuring quality at every layer.
- Develop dbt models, tests, and docs serving cross-functional stakeholders.
- Drive modelling decisions — dimensional models, snapshots, SCDs — across Exchange and Market Data.
- Design and maintain production data pipelines using Apache Airflow.
- Improve pipeline observability, alerting, and SLA monitoring; champion reliability practices.
- Mentor engineers via design reviews, pairing, and documentation.
- Evaluate new tools or patterns (streaming, real-time views) where they add value.
- Collaborate with the team’s AI specialists to deliver AI-driven Data Platform capabilities.
Requirements
What you’ll need- 6+ years in Data Engineering, with 2+ years in a senior or lead capacity.
- Pragmatic problem-solver — you set direction, unblock others, and make trade-offs.
- Strong communicator — can whiteboard architecture and narrate data stories alike.
- Deep expertise in SQL, Python, and modern tooling (dbt, Airflow, BigQuery or equiv.).
- Strong data modelling fundamentals — you think in schemas, grain, and lineage first.
- Production GCP experience (BigQuery, GCS, GKE, IAM) or comparable cloud platforms.
- Solid grasp of Kubernetes concepts (pods, Helm charts, resource management).
Benefits
Comp & perks- Health insurance
- Professional development opportunities
- Flexible work arrangements
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLPythondbtApache AirflowBigQuerydata modellingdimensional modelssnapshotsSCDsproduction data pipelines
Soft Skills
problem-solvingcommunicationmentoringcollaborationdirection settingunblocking otherstrade-off makingdesign reviewsdocumentationnarrating data stories
