Senior Analytics Engineer
About The Position
Design, develop, and maintain scalable ELT pipelines using Fivetran, Airflow, and custom integrations. Model raw data into clean, reliable datasets in the cloud data warehouse (BigQuery). Build and maintain LookML and data pipeline models that transform raw data into usable datasets for reporting and analysis. Own and improve the semantic layer and data documentation for self-service tools, creating a single source of truth for metrics and dimensions used across the company. Own the instrumentation and tracking plan across digital products using Segment. Work closely with product and engineering teams to ensure data integrity. Collaborate with engineers and business stakeholders to define clean data definitions and business logic. Partner with stakeholders to understand data needs. Help translate business questions into scalable data solutions, including presentations, well-designed data visualizations, and interactive dashboards. Monitor data pipelines for performance and accuracy and proactively resolve data issues.
Requirements
- Bachelor’s degree in Data Science, Engineering, or a related field plus three years of experience Analytics Engineering.
- Experience must include three years each of the following: owning business intelligence tooling end-to-end and leading cross-functional data projects; defining and enforcing KPI frameworks; working with SQL and data modeling in modern cloud data warehouses such as BigQuery; Looker (LookML), including semantic modeling, persistent derived tables (PDTs), and advanced dashboarding; performing data pipeline orchestration using Airflow or similar DAG manager; Python for data analysis, scripting, and automation, including pandas and NumPy; version control tools such as Git for deployment workflows; agile methodologies for project management and prioritization; and managing event tracking though a Customer Data Platform such as Segment.
- Experience may be gained concurrently.
Responsibilities
- Design, develop, and maintain scalable ELT pipelines using Fivetran, Airflow, and custom integrations.
- Model raw data into clean, reliable datasets in the cloud data warehouse (BigQuery).
- Build and maintain LookML and data pipeline models that transform raw data into usable datasets for reporting and analysis.
- Own and improve the semantic layer and data documentation for self-service tools, creating a single source of truth for metrics and dimensions used across the company.
- Own the instrumentation and tracking plan across digital products using Segment.
- Work closely with product and engineering teams to ensure data integrity.
- Collaborate with engineers and business stakeholders to define clean data definitions and business logic.
- Partner with stakeholders to understand data needs.
- Help translate business questions into scalable data solutions, including presentations, well-designed data visualizations, and interactive dashboards.
- Monitor data pipelines for performance and accuracy and proactively resolve data issues.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
