Senior Analytics Engineer
Own and scale transformation pipelines that convert diverse financial and operational data into reliable FP&A-ready models. The role requires strong SQL and dbt expertise, data integrity and performance skills, and effective collaboration across Engineering and Customer Success.
About the job
Responsibilities
- Own and scale client-facing data transformation workflows as integrations and customers grow, including effective use of AI.
- Design and evolve data integrity tests with Engineering and Customer Success.
- Partner with Customer Success to understand reporting needs, troubleshoot issues, and build robust transformations across diverse sources.
- Refactor and optimize critical data models and pipelines; establish reusable patterns and conventions.
- Improve code quality, documentation, team processes, and developer experience through reviews and clear communication.
- Coach teammates and contribute to hiring and onboarding.
Requirements
- Experience owning transformation pipelines for financial or operational data end to end, from source integration through production-ready models.
- Strong SQL and experience with dbt or similar transformation tools.
- Understanding of data across the source-to-consumption pipeline, with sound technical decision-making.
- Experience with version control, testing, and deployment.
- Ability to work independently through ambiguity and influence architectural decisions and engineering standards.
- Strong focus on code quality, data integrity, performance, and documentation.
- Clear communication with technical and non-technical stakeholders.
Nice to Have
- Experience working with financial data.
- Familiarity with the listed data, integration, and observability stack.
Compensation
- Annual salary range: $86,000–$192,000 USD.
Skills
SQL, dbt, Python, BigQuery, Airbyte, Fivetran, Merge, Datadog, Git, CI/CD, Data Modeling, Data Pipelines, Data Integrity Testing
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