Senior Data Analytics Engineer

Senior Data Analytics Engineer to build the data foundation that powers trustworthy reporting, self-serve insights, and data-driven decision-making across the organization.

A ground‑floor opportunity to own the core analytics engineering layer end‑to‑end—from defining foundational metrics and scalable data models to implementing best practices that will support long‑term growth.

This is a senior individual contributor role where you’ll lead through technical ownership, influence, and execution while setting standards future hires will build upon.

• Execute the analytics engineering roadmap, prioritizing high‑leverage data initiatives
• Design and implement a single source of truth using scalable data models (dimensional modeling, star schemas, modular marts)
• Develop canonical business definitions and standardized metrics across teams
• Manage and evolve a modern analytics stack (dbt, Snowflake, Git, CI/CD workflows)
• Establish best practices for modeling, testing, documentation, naming conventions, and dataset ownership
• Improve trust in data through quality checks, observability, and clear guidance on trusted datasets
• Partner cross‑functionally with Product, Engineering, Finance, and GTM to deliver impactful data solutions

• Build curated datasets and semantic‑friendly layers that support consistent BI and reporting
• Develop dashboards and analytics tools that empower stakeholders to self‑serve confidently
• Translate ambiguous business questions into structured, scalable data products (not one‑off analyses)
• Communicate analytical findings clearly and provide actionable recommendations

• Serve as the analytics engineering voice in architectural and technical decisions
• Drive cross‑functional projects from discovery through delivery
• Promote data literacy through documentation, metric definitions, and enablement
• Collaborate with product leaders during discovery to identify high‑impact data opportunities

• 5–8+ years in analytics engineering, data engineering, BI, or related roles
• Advanced SQL proficiency and experience with modern cloud warehouses (Snowflake preferred)
• Strong hands‑on experience with dbt (or similar frameworks), including modular design, testing, and documentation
• Deep experience designing scalable data models (star schemas, canonical metrics, shared dimensions)
• Experience supporting reliable reporting via BI tools (Looker, Tableau, Mode, etc.)
• Working knowledge of Python for scripting and automation

• Experience owning pipelines from ingestion through BI consumption
• Familiarity with Git workflows and CI/CD practices for analytics code
• Experience implementing data quality and reliability frameworks (dbt tests, monitoring, SLAs, etc.)
• Strong understanding of modern data architecture tradeoffs and scaling strategies

• Proven ability to translate vague business needs into structured data solutions
• Strong communication skills and ability to align stakeholders on definitions and outcomes
• Excellent prioritization skills, focusing on high‑impact work
• Comfortable operating in ambiguity while maintaining quality and trust

• Semantic modeling layers (LookML or similar)
• Workflow orchestration tools (Airflow, Dagster, Hevo, etc.)
• Startup or high‑growth tech environments
• Data cataloging or metadata management tools
• Statistical analysis or experimentation experience
• Exposure to AI/ML applications

This is a rare opportunity to define and scale the analytics function at a growing organization. You’ll have the autonomy to establish standards, influence tooling decisions, and make an immediate impact on business outcomes.

If you thrive at the intersection of strategy and hands‑on execution—and enjoy building scalable systems from the ground up—this role offers meaningful ownership and visibility.