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About the Role
We are looking for a Data Engineer to own and scale the data platform that powers analytics, reporting, and AI across Collective. You will design, build, and maintain the pipelines that move data from our product, financial, and third-party systems into our BigQuery warehouse; model that data into clean, well-documented, reliable tables; and set the engineering standards that keep the platform trustworthy as the company grows. You will join the Data Engineering team within Engineering and work closely with product engineers, analysts, and business stakeholders across Operations, Finance, and Go-to-Market. This is a hands-on role for someone who cares about data quality, takes ownership of production systems end-to-end, and wants their work to be the foundation the rest of the company builds on.
Responsibilities
- Design and build data pipelines, including developing, deploying, and maintaining scalable batch and event-driven pipelines that ingest data from application databases, SaaS tools, and external APIs into BigQuery using managed connectors, custom Python loaders, and orchestration tooling.
- Model the data by designing and implementing dimensional and analytical data models in dbt, following a layered architecture with clear grain, naming conventions, and documentation.
- Own data quality and reliability by implementing testing, monitoring, alerting, and data contracts across the pipeline; define and meet freshness and accuracy SLAs; triage and resolve pipeline failures and data incidents.
- Optimize performance and cost by tuning warehouse queries, partitioning, and clustering; managing BigQuery spend; and keeping pipelines efficient.
- Establish engineering standards by driving best practices for version control, code review, CI/CD, and infrastructure-as-code; document systems and runbooks.
- Govern and secure data by implementing access controls, PII handling, and data retention practices; partner with Security and Legal on compliance requirements.
- Enable the business by partnering with product engineers on source schema design and change management, and with analysts and stakeholders to translate business questions into reliable datasets, metric definitions, and self-serve reporting.
- Support AI and analytics use cases by maintaining the semantic layer, metric definitions, and documentation that allow LLM-based tools and internal agents to query the warehouse accurately and consistently.
Requirements
- 5+ years of professional experience in data engineering, analytics engineering, or a closely related role, ideally at a B2B SaaS or fintech company.
- Expert-level SQL and strong Python skills for building pipelines, transformations, and tooling; comfortable writing tested, production-grade code.
- Hands-on production experience with a cloud data warehouse (BigQuery strongly preferred), dbt or equivalent transformation framework, managed ingestion tools (Fivetran or similar), and an orchestrator (Airflow, Dagster, Cloud Composer, or similar).
- Deep understanding of dimensional modeling, layered warehouse architecture, and schema design, with strong opinions on grain, naming, and consistency.
- Experience implementing testing frameworks, lineage, monitoring, and alerting for data pipelines, and operating them in production including on-call.
- Fluency with git-based workflows, code review, CI/CD, and infrastructure-as-code; treat data infrastructure as software.
- A track record of taking ambiguous, high-impact problems and delivering reliable systems end-to-end, with a focus on outcomes rather than just implementation.
- Ability to explain technical trade-offs to non-technical stakeholders and drive alignment on data definitions across teams.
Skills
- SQL
- Python
- BigQuery
- dbt
- Fivetran
- Airflow
- Dagster
- Cloud Composer
- Git
- CI/CD
- Infrastructure-as-code
- Metabase
- Pub/Sub
- Kafka
- Amplitude
- Terraform
- Google Cloud Platform
- Datadog
- Claude Code
Location
- San Francisco
Work Type
- Hybrid
- Full-time
Experience Level
- 5+ years
Benefits
- Hybrid Work Model with in-office and remote flexibility
- Fresh Lunch provided on in-office days
- $150 monthly reimbursement for transit expenses
- $200 quarterly reimbursement for health & wellness
- Flexible PTO plus 14 company holidays
- 100% medical, dental, and vision coverage for employees
- 75% coverage for dependents' health, dental, and vision
- 16 weeks fully paid parental leave
- 401k plan
- Equity package
- Quarterly virtual events
- Annual in-person summit
About the Company
- Collective is on a mission to redefine the way businesses-of-one work.
- Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform.
- We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.
- Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more.
- Backed by General Catalyst, Sound Ventures, QED Investors, Google’s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft.