Staff Data Engineer
New
J
JobgetherData Engineering
Based in United StatesFull-TimeStaff
SalaryBase salary of $221,000–$276,000 for the San Francisco Bay Area and NYC Metro; $200,000–$257,000 for Washington D.C., Boston, Los Angeles Metro, and Seattle; $191,000–$238,000 for Denver, Chicago, Atlanta, and other U.S. metropolitan areas.
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Job Details
- Required Skills
- Snowflakedbt
Requirements
- Staff-level experience in data platform engineering, including the ability to establish architecture across teams and independently navigate complex stakeholder environments.
- Deep production experience with dbt and modern cloud data warehouses, with strong understanding of data transformation and warehouse architecture.
- Experience working with modern data orchestration platforms; hands-on Dagster experience is highly desirable.
- Practical experience with managed data ingestion and reverse ETL tooling.
- Strong understanding of data-platform reliability, security, access controls, data quality, scalability, and cost optimization.
- Ability to translate ambiguous business needs into clearly scoped, prioritized technical initiatives with measurable outcomes.
- Strong ownership mindset and ability to operate independently while collaborating effectively across engineering and business teams.
- Comfortable contributing to and working in the open on a public codebase or open-source environment.
Responsibilities
- Own the internal data platform end to end, including Snowflake architecture, capacity planning, cost management, dbt transformations, and orchestration standards in Dagster.
- Lead the ingestion ecosystem using tools such as Fivetran, Sling, dlt, and AWS DMS, as well as reverse ETL solutions including Hightouch and Census.
- Own warehouse access controls and data security, particularly as MCP-based workflows increasingly interact with organizational data.
- Design platform architecture that reduces cross-team dependencies, minimizes homegrown ingestion debt, and establishes a sustainable change-data-capture approach.
- Drive platform reliability through Dagster-based alerting, data quality practices, operational monitoring, and cost management.
- Take ownership of deferred data-platform work, including one-off ingestion, data enablement, and growth-related initiatives.
- Partner with engineering teams on SLA-critical pipelines such as billing and consumption pricing.
- Work extensively with Dagster and bring practical platform learnings and feedback to the product team.
- Define requirements, establish priorities, shape the roadmap, and work directly with stakeholders across multiple organizational functions.
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