The team is looking for a Senior Analytics Engineer to help scale and mature our data warehouse and analytics platform. This role focuses on building reliable, well-modeled datasets that power reporting, analytics, and downstream tools across the company.

You’ll work hands-on in BigQuery, develop SQL-based transformation layers, and help evolve our Prefect-orchestrated data workflows. You’ll also partner closely with the rest of the team to improve the robustness, performance, and scalability of our warehouse models and tables.

What You’ll Do:

• Design, build, and maintain scalable data models in our BigQuery-based data warehouse.
• Develop and improve SQL-based transformation layers, with an emphasis on clean, well-documented dimensional models.
• Contribute to and extend Python-based data infrastructure supporting orchestration, monitoring, and reliability.
• Ensure data quality, consistency, and usability for downstream analytics and reporting.
• Support and enhance our BI ecosystem, with data consumed through Looker ML and Power BI.
• Collaborate with engineering, product, and business stakeholders to translate analytical needs into durable data structures.

What We’re Looking For:

• 5+ years of experience in data engineering, analytics engineering, or a related role.
• Strong SQL skills and deep experience designing dimensional models (facts, dimensions, marts).
• Hands-on experience with modern data warehouses, ideally BigQuery.
• Experience using DBT or similar transformation frameworks.
• Working knowledge of Python for data pipelines, orchestration, or backend data tooling.
• Experience building or supporting production analytics workflows and BI consumption.
• A pragmatic mindset: you care about correctness, scalability, and helping the business actually use the data

Bonus Points For:

• Experience with Prefect, Airflow, or other workflow orchestration tools.
• Familiarity with Looker / LookML.
• Experience supporting Power BI users or other external BI consumers.
• Exposure to data quality checks, testing frameworks, or observability tools.
• Startup or small-team experience where adaptability and ownership are key.

Our Data & Analytics Stack:

• Data Warehouse: BigQuery.
• Transformations: SQL, DBT.
• Orchestration: Prefect.
• Infrastructure & Tooling: Python, Gitlab.
• BI & Analytics: Looker ML, Power BI.