Senior Data Engineer

What You Bring to The Team

• Data Engineering Experience: 6+ years of professional experience in Data Engineering, with a demonstrated track record of hands-on delivery and end-to-end ownership of scalable, high-quality data platforms.
• Modern Cloud Data Mastery: Deep, production-grade experience with Snowflake (strongly preferred) or comparable warehouses such as BigQuery or Databricks. You must have a strong command of the cost and performance implications of data design and query patterns.
• Expert SQL & dbt Skills: Advanced SQL capabilities for writing and optimizing complex queries, paired with extensive hands-on experience in data transformation, dimensional modeling, and implementing quality checks and testing frameworks in dbt.
• Mentorship & Influence: Experience actively supporting the growth of others, with a proven ability to mentor peers and contribute to a healthy, collaborative engineering culture.
• End-to-End Ownership: A history of taking projects from initial ambiguity through to production, including CI/CD integration, automated testing, and ongoing data quality ownership.
• Clear Communication: The ability to articulate complex data concepts and technical trade-offs to both engineering peers and non-technical stakeholders.
• AI Readiness: A willingness to work with AI-assisted development tools as part of your daily workflow. You don't need to be an expert today, but you should be curious, open to learning, and able to critically evaluate AI-generated outputs before they reach production.
• Exceptional Communication: Strong ability to work closely with finance and non-technical stakeholders, translating complex business logic into clean, reusable datasets.

Nice to Haves

• Finance Domain Expertise: Experience working with highly regulated financial/accounting data, understanding financial modeling logic, or integrating ERP systems (e.g., NetSuite, Sage) to serve finance stakeholders.
• Data Activation Experience: Hands-on experience with reverse ETL tools (e.g., Hightouch, Census) to operationalize data and drive it back into business applications.
• Advanced Tooling Familiarity: Experience with orchestration tools (e.g., Airflow) and building Snowflake semantic views.
• Legacy Migration Experience: Proven ability to audit, understand, and migrate legacy reporting systems into a modern, structured data stack.
• Programming Skills: Familiarity with Python, Go, or Scala for custom data processing