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Role Description

The Senior Data and Analytics Engineer will own the transformation and semantic layer of the company’s enterprise data platform. This role is responsible for designing, building, and maintaining scalable dimensional models and curated datasets within Snowflake that power financial and operational reporting across all operating companies.

This is a hands-on engineering role for someone who lives in SQL and dbt, thinks deeply about data grain and business logic, and takes pride in building clean, reliable reporting infrastructure. The role translates business requirements into well-structured data models and ensures that enterprise metrics are accurate, documented, and trusted.

Key Responsibilities

• Design and maintain scalable fact and dimension models, define grain, and implement enterprise metric logic using SQL and dbt within Snowflake.
• Develop, test, and optimize transformation workflows to ensure clean, reliable, and performant datasets that support financial and operational reporting.
• Partner with Finance and Operations to translate business requirements into technical models, ensuring metric definitions are accurate and consistently applied.
• Establish validation checks and reconciliation processes to ensure reporting outputs tie to source systems and financial statements.
• Publish curated datasets and support dashboards in Sigma or Power BI, enabling self-service analytics while maintaining governance standards.
• Work closely with internal or external data engineering resources to define schema expectations, monitor ingestion quality, and resolve upstream data issues.

Qualifications

• 4+ years of experience in analytics engineering, data engineering, or business intelligence engineering roles
• Advanced SQL skills with daily hands-on experience building complex transformations
• Strong experience with dbt and modern ELT workflows
• Deep understanding of dimensional modeling (fact/dimension design, grain definition, star schemas)
• Experience working in Snowflake or similar cloud data warehouse environments
• Experience building reporting infrastructure (not primarily ML/data science focused)
• Strong understanding of financial and operational reporting concepts
• Experience in high-growth, multi-entity, or PE-backed environments preferred

Requirements

• Writes clean, efficient SQL and builds well-structured, scalable models
• Understands data grain, relationships, and how business logic translates into dimensional architecture
• Proactively validates outputs and ensures reporting accuracy
• Converts operational and financial requirements into precise, reusable technical logic
• Takes responsibility for the reliability and integrity of the semantic layer

Benefits

• Competitive compensation commensurate with experience
• Comprehensive benefits package including healthcare
• 401(k) match
• Flexible time off