Sr. Staff Systems Engineer

Oakland, California, United States, AMER · USA - Oakland · 10+ years experience · Hybrid · Posted Oct 6, 2026

At a glance

Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

The Senior Staff Systems Engineer, Data and Integrations will set the technical direction for the data that powers Fivetran's business operations.
This role involves owning the canonical data models, system contracts, and pipelines that move data between marketing, sales, billing, and product operations systems.
The position requires leading large-scale data initiatives, such as system migrations and org consolidations, while mentoring engineers on data modeling and pipeline standards.

Own canonical data models for marketing, sales, billing, and product operations integrations.
Define team-wide standards for data modeling, data quality, testing, governance, and documentation.
Design integration architecture, establishing guidance for batch, real-time, and event-driven data movement.
Lead the design and execution of complex data initiatives including bulk migrations and system consolidations.
Build, review, and ship SQL and Python transformations and pipelines.
Design validation and reconciliation approaches for migrations and pipeline changes.
Design monitoring, alerting, and data quality frameworks to ensure data freshness and accuracy.
Lead root cause analysis on complex cross-system data issues.
Translate ambiguous business requirements into technical designs and data models.
Mentor other engineers and review their designs and code.

10+ years of experience in Data Engineering, Analytics Engineering, or a similar role.
Expert SQL proficiency, including complex transformations, performance tuning, and large-scale data reconciliation.
Strong proficiency in a general purpose programming language such as Python or TypeScript.
Hands-on experience with business systems data models such as Salesforce, NetSuite, Coupa, Workday, or Zendesk.
Experience with data migration, org merge, or major re-implementation.
Demonstrated experience designing and delivering large-scale ETL/ELT solutions.
Experience with data quality, validation, and governance frameworks.
Ability to lead through influence across technical and non-technical stakeholders.

Experience with dbt or a similar transformation framework.
Hands-on experience with iPaaS platforms such as Celigo, Workato, or Boomi.
Experience with reverse ETL tools.
Experience with cloud platforms such as AWS or GCP.
Experience with infrastructure as code and CI/CD for data pipelines.
Familiarity with AI/ML capabilities to augment data quality, matching, and automation.

Show all 14 skills