Job Title: Data Architect
Location: Oakland, CA (Onsite - Locals Only)
Duration: 6 months
About the Role
building data pipelines to power the modern data stack for thousands of companies. We re looking for a Senior Staff Systems Engineer, Data and Integrations to join our Systems Engineering team and set the technical direction for the data that runs Fivetran's business. In this role, you will own the data architecture behind our marketing, sales, billing, and product operations: the canonical data models, the contracts between systems, and the pipelines and transformations that move data reliably between them. You will lead our largest and most consequential data initiatives, such as system migrations, org consolidations, and re-platforming of core integrations, from design through validation and cutover.
This position sits at the crossroads of data engineering, data modeling, and business process. You will partner closely with our Systems, Analytics, and Engineering teams, as well as Marketing, Revenue Operations, Accounting, Product Operations, and other business partner teams, and you will mentor the engineers who build within the standards you set.
Technologies You ll Use
Our core systems are Salesforce, Netsuite, Coupa, Workday, and Zendesk, with BigQuery as our data warehouse. Our current integration stack includes Celigo and Fivetran itself. You should be an expert in SQL and strong in a general-purpose programming language such as Python or TypeScript, and comfortable evaluating and adopting new tools when necessary.
A data engineering background is required, with expertise in data modeling, ETL/ELT development, data quality testing, and data validation at scale. Experience with dbt or a similar transformation framework, and with API-based and event-driven integration patterns, is preferred. Help us bring established data engineering practices to internal business systems, and define what those practices should be here.
What You ll Do
Data Architecture and Standards
Own the canonical data models for marketing, sales, billing, and product operations integrations, and define how business concepts map to data across our core systems.
Define team-wide standards for data modeling, data quality, testing, governance, and documentation, and drive their adoption across Systems Engineering and partner teams.
Contribute to the design of integration architecture, establishing guidance for when to use batch, real-time, and event-driven data movement.
Delivery of Complex Initiatives
Lead the design and execution of our most complex data initiatives, including bulk migrations, system consolidations, and re-implementation of core integrations, from target-state design through validation, cutover, and stabilization.
Build, review, and ship the SQL and Python transformations and pipelines behind these initiatives, setting the bar for code quality on the team.
Design the validation and reconciliation approach for migrations and pipeline changes, and sign off with stakeholders that record counts, values, and business rules reconcile.
Reliability and Observability
Design the monitoring, alerting, and data quality framework that gives end-to-end visibility into data freshness and accuracy across systems, and define the KPIs used to measure integration and data health.
Lead root cause analysis on the most complex cross-system data issues, and drive the systemic fixes that prevent recurrence.
Business Partnership Technical Leadership
Translate ambiguous requirements from cross-functional business partners into data models and technical designs, and drive alignment across teams with competing priorities.
Serve as the technical lead and subject matter expert for business data within the Systems Engineering team.
Mentor other engineers and review their designs and code, raising the team's proficiency in data modeling, testing, and pipeline design.
Write and maintain design documents and data flow documentation for current and target state, so decisions are legible to the team and to partners.
Skills We re Looking For
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.
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, with experience building production-grade, tested data pipelines.
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.
Demonstrated experience designing and delivering large-scale ETL/ELT solutions and the data quality, validation, and governance frameworks around them.
Ability to evaluate trade-offs between short-term delivery and long-term data architecture health, and to communicate those decisions clearly.
Ability to lead through influence, driving alignment across technical and non-technical stakeholders without direct authority.
Bonus Skills
Experience with dbt or a similar transformation framework.
Hands-on experience with iPaaS platforms such as Celigo, Workato, or Boomi, and with reverse ETL tools, including experience choosing between them.
Experience with cloud platforms such as AWS or Google Cloud Platform, infrastructure as code, and CI/CD for data pipelines.
Familiarity with AI/ML capabilities to augment data quality, matching, and automation.
