Data Engineer
Skills
AnalyticsConflictConnectorsDimensional ModelingDownstream Oil And GasEvolutionModeling
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 3+ years in data engineering analytics engineering or closely related engineering role
- Production-quality Python and advanced SQL skills
- Experience designing building and operating Airflow workflows
- Strong dbt and dimensional modeling fundamentals
- Built custom integrations against APIs webhooks files or event streams
- Deep knowledge of API ingestion including authentication pagination rate limits incremental sync retries and backfills
- Owned a business-critical pipeline through production support with monitoring alerting logging reconciliation CI CD and runbooks
- Experience in a high-growth environment ideally DTC or subscription
- Broad hands-on experience across the data stack
- Fluency using AI coding agents for implementation testing debugging refactoring and review
- BigQuery GCP and Cloud Composer experience is a plus
Nice to have
- Ownership
- High standards
- Fast mover
- Independent
- Strong judgment
- Clear communicator
Day to day
- Design and own data pipelines from source systems into the warehouse
- Build and operate Airflow DAGs for scheduled and event-driven workflows
- Develop dbt models and a governed semantic layer that supports analysts internal tools and AI agents
Hiring process
- Interview process