Lead the design, development, and maintenance of complex data pipelines, ensuring scalability, reliability, observability, and automation are built-in properties of the data system
Lead the definition and evolution of complex analytical and semantic models, integrating multiple sources and domains and ensuring semantic consistency, stability, and alignment with different consumption patterns
Define and guide the use of data stack tools, including orchestration, ingestion, and transformation, establishing technical standards, operational best practices, and long-term direction
Establish system-wide standards for quality, testing, and reliability to ensure predictable delivery, reduced regressions, and the long-term sustainability of production data solutions
Translate business needs into technical modeling rules, working directly with business stakeholders

Advanced SQL
Deep knowledge of dimensional modeling (Star Schema/Snowflake Schema) to structure data efficiently for analytics
Proficiency with dbt
Cloud Data Warehouse: experience with cloud data warehousing platforms such as Snowflake, BigQuery, Redshift, or Databricks
Experience using Git/GitHub for version control and collaboration, applying software engineering best practices
Ability to translate business requirements into data transformation rules and analytical models

Senior Analytics Engineer

Key skills