Senior Data Engineer

About the Role
We are looking for a Senior Data Engineer to join our growing data team. In this role, you will be a key contributor to our data infrastructure — designing and building the systems that power analytics, reporting, and business intelligence capabilities. You'll work across modern cloud data platforms, architect robust pipelines, and partner closely with analytics and engineering teams to ensure data is clean, reliable, and ready for consumption.

What You'll Do
Design, build, and maintain scalable data pipelines that ingest, transform, and deliver data across our cloud data ecosystem
Architect and implement data warehouse schemas optimized for performance, scalability, and analytical consumption
Prepare and model data to support BI tools and downstream reporting needs, ensuring data is accurate, well-documented, and easily accessible
Collaborate with data analysts, scientists, and business stakeholders to understand data requirements and translate them into robust engineering solutions
Work across multiple cloud data warehouse platforms as needed, applying best practices for each environment
Contribute to data governance practices including lineage, cataloging, and documentation
Identify and resolve data quality issues proactively
Mentor junior team members and contribute to engineering best practices



Requirements

What We're Looking For
5+ years of experience in data engineering
Hands-on, production-level experience with Snowflake (mandatory) — including schema design, performance optimization, and administration
Strong experience with at least one additional data warehouse platform; Google BigQuery experience is a strong plus
Solid understanding of data warehouse design principles — star schema, dimensional modeling, slowly changing dimensions, and similar patterns
Strong SQL skills — you are comfortable writing complex queries, optimizing for performance, and debugging data issues
Experience building and maintaining data pipelines using modern orchestration and transformation tools (e.g., dbt, Apache Airflow, Spark, or similar)
Proficiency in at least one programming language commonly used in data engineering (Python strongly preferred)
Expert knowledge of one or more relational or analytical databases (e.g., PostgreSQL, Redshift, SQL Server, or similar)
Experience working in cloud-native environments (AWS, GCP, or Azure)
Strong communication skills — ability to clearly explain technical concepts to both technical and non-technical stakeholders, and to collaborate effectively across teams



Benefits

Nice to Have
Experience with Google BigQuery, including working with large-scale datasets and optimizing query costs
Experience designing semantic data models or working within a semantic layer (e.g., LookML, dbt metrics, AtScale)
Hands-on experience with a BI tool such as Looker, Tableau, Power BI, or similar — particularly in structuring data to serve those tools effectively
Familiarity with data lakehouse patterns or platforms (e.g., Delta Lake, Apache Iceberg)
Experience with CI/CD practices applied to data infrastructure