Senior Data Engineer (Systems and Integrations)

Join Fivetran + dbt Labs as a Senior Data Engineer, where you will set the technical direction for the data that powers our business. You will own the data architecture behind our marketing, sales, billing, and product operations, leading our largest data initiatives from design through validation and cutover. This role requires expertise in data modeling, ETL/ELT development, and data quality testing, as well as strong proficiency in SQL and a general-purpose programming language such as Python or TypeScript.

USD 202,787 - 253,483

Responsibilities

• Ownership of the data architecture behind marketing, sales, billing, and product operations, including canonical data models and data pipelines.
• Leading complex data initiatives such as system migrations, org consolidations, and re-platforming of core integrations, from design through validation and cutover.
• Defining team-wide standards for data modeling, data quality, testing, governance, and documentation, and driving their adoption across Systems Engineering and partner teams.
• Strong proficiency in a general purpose programming language such as Python or TypeScript, with experience building production-grade, tested data pipelines
• Demonstrated experience designing and delivering large-scale ETL/ELT solutions and the data quality, validation, and governance frameworks around them

Requirements

• Ability to evaluate trade-offs between short-term delivery and long-term data architecture health, and to communicate those decisions clearly
• 10+ years of experience in Data Engineering, Analytics Engineering, or a similar role, with a deep focus on modeling and transforming business data and a track record of technical leadership on complex, multi-team initiatives
• Hands-on experience with business systems data models such as those for Salesforce, NetSuite, Coupa, Workday, or Zendesk, including a data migration, org merge, or major re-implementation
• Ability to lead through influence, driving alignment across technical and non-technical stakeholders without direct authority
• Expert SQL proficiency, including complex transformations, performance tuning, and large-scale data reconciliation
• Familiarity with AI/ML capabilities to augment data quality, matching, and automation
• Hands-on experience with iPaaS platforms such as Celigo, Workato, or Boomi, and with reverse ETL tools, including experience choosing between them

Preferred

• Experience with dbt or a similar transformation framework
• Experience with cloud platforms such as AWS or GCP, infrastructure as code, and CI/CD for data pipelines