Analytics Engineer II

What You’ll Do

• Build and maintain dbt models and core datasets that support Accounting reporting and downstream automation use cases.
• Improve platform reliability through strong testing patterns, alerting, and runbooks.
• Own and document data pipelines and lineage, ensuring changes are understandable and auditable.
• Identify, troubleshoot, and resolve production data issues, and drive root-cause fixes.
• Optimize performance and cost in Snowflake and dbt to support scaling needs.
• Partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets.
• Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows).

What We Look For

• 3+ years of experience in analytics engineering, data engineering, or similar roles working with production data systems.
• Strong SQL skills and hands-on experience building in dbt (modeling, testing, documentation).
• Experience operating in a modern development workflow:
• Git and pull-request based collaboration (GitHub preferred).
• Familiarity with standard IDEs and collaborative debugging practices.
• Experience working with cloud data warehouses (Snowflake preferred).
• A strong sense of ownership and comfort working in ambiguous, fast-moving environments.

Nice to Have

• Finance/accounting data familiarity (e.g., close concepts, reconciliations, ledger-style modeling).
• Experience with integration/automation platforms (Workato, Fivetran, or similar).
• Experience supporting reporting layers and BI tooling.
• Working knowledge of Python for data manipulation and automation.
• Familiarity with CI pipelines and quality gates for code quality, testing, and build validation.
• Interest in applying AI-assisted development responsibly within engineering guardrails.