Senior Analytics Engineer

Job Description Senior Analytics Engineer Summary/objective

The Senior Analytics Engineer is considered a leading role in shaping the analytics platform, data modeling practices, and decision-enabling systems  a senior individual contributor, you will act as a technical and strategic thought partner across the business—working with data engineers, analysts, and product teams to turn raw data into reliable, governed, and insightful data assets.

This is a hands‑on, high‑impact role that requires deep expertise in data modeling, dbt, and cloud‑based data stacks, along with a strong product mindset and ability to partner closely with stakeholders to drive business value.

• Lead the design and evolution of our semantic layer and analytics data models using dbt and modern warehouse platforms.
• Define and enforce best practices in data transformation, versioning, testing, and documentation.
• Collaborate closely with analysts, product managers, and data engineers to align modeling work with business use cases.
• Own the lifecycle of metrics and definitions, ensuring consistency, trust, and reusability across the organization.
• Drive the implementation of self‑service data capabilities, empowering teams through curated datasets and intuitive tooling.
• Provide technical mentorship and guidance to analytics engineers and analysts across teams.
• Act as a bridge between analytics and engineering, translating requirements into scalable and performant data infrastructure.
• Contribute to governance initiatives (e.g., data cataloging, lineage, quality monitoring) to increase trust in data products.
• Optimize and tune warehouse performance for cost and scale (Databricks preferred, Big Query, Snowflake, etc).

Having wide‑ranging experience using professional concepts and company objectives to resolve complex issues creatively and effectively. They are the go‑to expert in one specific area of their role. Some barriers to entry exist at this level (e.g., dept/peer review)—the level at which a career may plateau.

Works on complex issues where analysis of situations or data requires an in‑depth evaluation of variable factors. Exercises judgment in selecting methods, techniques, and evaluation criteria for obtaining results. Networks with key contacts outside their own area of expertise.

Determines methods and procedures on new assignments and may coordinate activities of other personnel.

Typically requires a minimum of 6 years of related experience with a bachelor's degree; 6 years and a master's degree; or equivalent experience.

• 7+ years of experience in analytics engineering, data engineering, or data analytics roles.
• Expert in dbt and modern data transformation pipelines (dbt Cloud or Core)
• Deep understanding of data modeling techniques (dimensional modeling, star/snowflake schema, slowly changing dimensions, data vault, etc.)
• Proficient in SQL (performance tuning, complex joins, CTEs, window functions)
• Strong working knowledge of cloud data warehouses (e.g., Databricks preferred, Snowflake, Big Query, Snowflake, etc)
• Comfortable with Git‑based workflows, CI/CD, and software engineering best practices in analytics contexts
• Experience collaborating with cross‑functional teams and translating ambiguous business needs into structured data models
• Demonstrated experience owning data domains and metrics at scale
• Strong communication and storytelling skills; able to explain complex data topics to both technical and non‑technical audiences
• Proficient in Python

• Experience with modern BI tools (Power
  
  BI, Looker, Mode, Hex, Tableau, etc.)
• Some exposure to Spark
• Background in experimentation (e.g., A/B testing infrastructure and analysis)

Prolonged periods of sitting at a desk and working on a computer. Must be able to lift up to 15 pounds.

Yes, up to 15% domestic travel may be required.

Employee must be legally authorized to work in the United States.

Exempt

Office/Hybrid/Remote

Senior Analytics Engineer

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