Senior Analytics Engineer

What You Will Work On

• Transform raw data into high-quality data models that are easily queried and understood by various business units (e.g., Sales, Marketing, Product, Engineering, Operations)
• Design, build, and maintain our semantic layer using Snowflake semantic views — defining metrics, entities, and business logic so stakeholders can self-serve trustworthy, consistently-defined data without re-deriving logic
• Partner with analysts and business teams to build and govern BI content in Tableau and Redash — curated data sources, certified dashboards, and reusable metrics — and reduce dashboard sprawl through consolidation and clear standards
• Partner directly with stakeholders to translate business questions into data requirements, co-develop metric definitions, and drive adoption of governed models and dashboards
• Proactively identify opportunities to close gaps in reporting and insights generation by architecting new business facts and dimensions
• Apply effective data testing and sensitive data management strategies to ensure the quality and security of information provided to the business
• Level up our information design, data governance, and analytics engineering practices by defining our internal standards for lineage, maintainability, performance, and cost management
• Provide technical leadership and mentorship to junior and mid-level team members, fostering best practices in data modeling, orchestration, data warehouse architecture, data privacy, and analytics enablement

Qualifications

• A minimum of 5 years of professional hands-on experience in analytics engineering, data analytics, data engineering, or a similar role
• Extensive experience transforming raw data into consistent, trustworthy data models for use by analytics and business stakeholders
• Hands-on experience building and maintaining a semantic/metrics layer (Snowflake semantic views or equivalent) that powers self-service analytics
• Demonstrated experience building and governing assets that power BI— certified data sources, dashboard design, and self-service enablement
• Proven track record partnering directly with non-technical stakeholders to define metrics, gather requirements, and drive adoption of data products
• Proficient in writing performant SQL and leveraging dbt for data transformation and model management
• Expert understanding of data warehousing concepts for analytics, including dimensional modeling, star schemas, and representation of complex business facts
• Experience with Python or other programming languages commonly used in data engineering
• Strong ability to troubleshoot, optimize, and scale data models for performance and usability
• Comfortable translating complex technical topics for business stakeholders
• Comfortable with Git, command line, and CI/CD best practices
• Comfortable managing workflows using Agile practices
• Ability to solve ambiguous problems independently

Nice to Have

• Experience w/modern data stack tools (e.g., Fivetran, dbt, Snowflake)
• Experience working in complex, highly dimensional data ecosystems
• Experience implementing sensitive data management solutions and privacy-by-design principles strongly preferred

Technologies Used

• Languages: SQL, Python, Terraform
• Stack: Snowflake (incl. semantic views), Airflow, Fivetran, dbt, GitHub, CircleCI, Tableau, Redash, Jira

Compensation

• The base wage range for this position based in our New York City Office is targeted at $147,000.00 - $190,000.00 per year.