This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Engineer based in United States.
This is a high-impact Staff-level role owning the internal data platform end to end during a major data-stack consolidation.
You will lead the architecture and evolution of a modern platform built around Snowflake, dbt, and Dagster.
The role combines deep technical ownership with cross-functional partnership and independent decision-making.
You’ll shape platform standards, reliability, security, cost efficiency, ingestion, and data accessibility across the organization.
You’ll also help reduce technical debt and dependencies so teams can move faster and operate with greater confidence.
Part of the work will be developed openly, creating a public reference implementation of the organization’s own data platform.
You’ll join a remote-first, high-performance environment that values ownership, thoughtful collaboration, and meaningful technical impact.
Accountabilities:
- 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, while respecting engineering ownership of those systems.
- 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.
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.
Benefits:
- Base salary of $221,000–$276,000 for the San Francisco Bay Area and NYC Metro.
- Base salary of $200,000–$257,000 for Washington D.C., Boston, Los Angeles Metro, and Seattle.
- Base salary of $191,000–$238,000 for Denver, Chicago, Atlanta, and other U.S. metropolitan areas.
- Actual compensation within the applicable range depends on location, experience, and qualifications; equity and benefits are provided separately.
- Remote-first work environment with a flexible-first culture.
- Equity stock options.
- 401(k) with a 5% company match and immediate vesting.
- Unlimited paid time off.
- Medical, dental, and vision insurance.
- Generous parental leave.
- Life insurance and disability benefits.
- $800/month remote work stipend.
- Opportunities to work on open-source infrastructure and high-impact internal data systems.
- Inclusive environment focused on belonging, equal opportunity, professional growth, and meaningful contribution.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
#LI-CL1
