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Senior Data Engineer

Alchemy· *Engineering
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Hybrid (New York), Hybrid (Remote), Hybrid (San Francisco)$205k - $230kFull-timePosted 1w ago

About the role

Build and run the internal data platform to understand product usage, revenue, and cost of serving customers. Own ingestion, schema changes, data quality, and collaboration with analytics partners to define datasets for reporting, analytics, and AI-assisted tools.

Responsibilities

  • Build batch and streaming pipelines that connect operational databases, product events, billing systems, and external sources to the internal data platform.
  • Make ingestion recoverable through change-data capture, schema-change handling, idempotent processing, and safe backfills.
  • Operate and improve Snowflake, including access controls, workload management, query performance, and compute and storage costs.
  • Improve orchestration and deployment workflows so engineers can test, ship, and debug pipelines safely.
  • Build data-quality checks that detect stale, missing, duplicated, or inconsistent records before they reach downstream consumers.
  • Work with analytics partners on shared data models, source definitions, and documentation. Make dataset ownership and upstream dependencies clear.
  • Reduce recurring manual work and build reusable tools for self-service data access.
  • Participate in production support and incident response for pipelines and the data platform. Restore data flow, reconcile affected datasets, and fix the causes of recurring failures.

Qualifications

  • Experience independently building and operating production data pipelines and the infrastructure around them.
  • Strong SQL and Python skills, including testing, debugging, and maintainable software design.
  • Experience with Snowflake or a comparable warehouse, including performance tuning and access management.
  • Experience with workflow orchestration and transformation tools such as Airflow and dbt, or equivalent systems.
  • Understanding of data modeling, incremental processing, schema evolution, and data-quality testing.
  • The ability to trace a data discrepancy from a downstream report back to its source, explain the cause, and fix it.
  • Good judgment about stakeholder needs: turn recurring requests into reusable datasets or tooling, and make trade-offs clear.

Skills

Required:SQLPythonSnowflakeAirflowdbt

Benefits

  • Private Health Insurance
  • Gym Reimbursement
  • Commuter Benefits
  • Flexible Time Off
  • In-Office Group Meals
  • Learning & Development Stipend
  • Company Sponsored Conferences & Events
  • Books & Audiobook subscription with Bookster
Last updated Oct 25, 2026. Interested? Apply on the company site.
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About Alchemy

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