Senior Data Engineer

About the role

The company is expanding its data engineering capacity to keep pace with growth in its product portfolio and analytical demand. The Senior Data Engineer builds and maintains the models, pipelines, and platform components that make company data trustworthy and usable, taking assigned workstreams from investigation through design, implementation, and support.

Key responsibilities

• Design and build dimensional and analytical models in dbt against a cloud data warehouse across core domains and new business lines.
• Develop and maintain ingestion and orchestration pipelines using dbt Core, Snowflake SQL, and Python, ensuring reliable scheduled execution.
• Profile source data from transactional systems and third‑party integrations to determine grain, keys, and business meaning, documenting assumptions.
• Implement data quality tests, monitoring, and alerting to catch anomalies before they affect reports or customer‑facing outputs.
• Diagnose production data issues across ingestion, transformation, and source layers, documenting root causes for the team.
• Participate in design and code reviews with engineers across regions, providing and receiving substantive technical feedback.
• Partner with analysts and stakeholders to clarify requirements and validate results.

Required profile

• 5+ years of data engineering experience, including 3+ years building analytical models in a cloud data warehouse.
• Advanced SQL skills, especially with Snowflake, for writing, debugging, and optimizing complex analytical queries.
• Production‑grade dbt experience: model layering, testing, documentation, incremental strategies, version‑controlled projects.
• Proficiency in Python for pipeline development, API/file integrations, and orchestration with Airflow or equivalent.
• Demonstrated ability to investigate undocumented source systems and map data to real business processes.
• Familiarity with dimensional modeling and trade‑offs between normalized, wide, and aggregate structures.
• Experience with Git‑based development, pull‑request review, and CI/CD pipelines.
• Exposure to BI tools (Tableau, Looker, Power BI) to model data that serves reporting well.
• Clear written and spoken English with strong asynchronous communication habits.
• Conscientious about data accuracy and willing to raise questions when data looks incorrect.

Required skills

• dbt
• Snowflake
• SQL
• Python
• Airflow (or equivalent orchestration tool)
• Git
• CI/CD pipelines
• Tableau
• Looker
• Power BI
• Dimensional modeling