PadSplit is growing its analytics platform and needs a hands-on Sr. Data Engineer to work alongside our existing DE lead. This person will build and maintain ingestion and transformation pipelines across Dagster (or Airflow), dbt, and Snowflake, with supporting work in Python, Airbyte, and AWS. The role combines building new pipelines and data models with providing real coverage on critical paths — especially the daily Postgres → Snowflake → dbt flow and third-party API loads — all shipped through reviewed pull requests rather than one-off scripts.
We’re looking for a practitioner who thinks natively in dimensions, facts, and slowly changing dimensions — someone who knows when to use a full refresh versus an incremental load and how that choice affects idempotency and backfills. This person writes clear, reviewable PRs and gives equally thoughtful reviews, with attention to scoped diffs, sensible tests, and failure modes. They’re comfortable in complex Python data flows and have enough AWS literacy to reason about task roles, buckets, and cross-account access without needing to own all of platform engineering.
Compensation is based on the role’s scope, national market benchmarks, the person’s expertise and experience, and the impact of their contributions to our business goals.
Notice to Applicants:
All employees must be able to establish their identity and authorization to work in the United States by completing Form I-9 after an offer of employment. For this role, we are unable to provide employment-based visa sponsorship, now or in the future. Applicants must be authorized to work in the U.S. without requiring sponsorship from PadSplit. Candidates who are U.S. citizens, lawful permanent residents, refugees, asylees, and others with unrestricted work authorization are welcome to apply. PadSplit is an equal opportunity employer and does not discriminate on the basis of citizenship status or national origin.
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