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Staff Analytics Engineer (Remote)

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Salary

$180,000 - $221,000

Location

Remote - United States

Posted

Yesterday

Rula is looking for a Staff Analytics Engineer to anchor our Universal Horizontal Platform Layer. Reporting directly to the Senior Engineering Manager, you will serve as the structural enforcer and architectural leader for our data ecosystem, guiding our domain engineers through an organization-wide migration to Snowflake and Medallion architectures.

This is a highly strategic, systems-level engineering role. You will balance deep technical execution with the professional backbone required to negotiate data contracts, push back on executive scope creep, and align platform infrastructure with Rula's broad business strategy.

What you'll do

  • Platform Architecture & Snowflake Migration: Lead the overarching design and execution of Rula’s migration to Snowflake, establishing the structural blueprints and Medallion execution playbooks that empower domain pods to build reliably without disrupting their delivery SLAs.
  • Strategic Scoping & Executive Partnership: Act as a critical technical bridge between engineering and business strategy. Utilize your strengths to directly negotiate technical boundaries with leadership, establish strict intake guardrails, and help guide the vision of the data landscape.
  • Warehouse Optimization & Cost Governance: Own Snowflake compute-cost profiling and warehouse performance globally. Establish and govern the financial and operational baselines for our cloud infrastructure to protect the balance sheet as our clinical data volume scales.
  • CI/CD Defense & Quality Assurance: Design, build, and strictly enforce automated CI/CD testing gates within GitHub to actively intercept query regressions, schema anomalies, and unoptimized code before pull request compilation.
  • Team-Scaled AI Multiplier: Drive technical leverage across the entire organization by systematically scaling the adoption of AI-assisted tools—such as productizing prompt banks, integrating AI into CI/CD code reviews, and automating boilerplate code generation—to accelerate total team delivery velocity.

Required qualifications

  • 6+ years of professional experience in analytics engineering, data architecture, or data engineering, with a proven track record of operating at a systems-level to drive organization-wide data strategies, cross-domain workflows, or platform architecture.
  • Experience leading the architectural design, optimization, or migration of a modern cloud data platform (Snowflake, Redshift, BigQuery) supporting multiple cross-functional business domains.
  • Expert-level SQL proficiency and production experience designing data models using Medallion architectures.
  • 2+ years of hands-on experience utilizing dbt to build, orchestrate, and test production-grade ELT pipelines.
  • Deep expertise in production git workflows with a proven ability to design, build, and enforce automated CI/CD testing gates.
  • Proven experience acting as a bridge between technical execution and business strategy, with strong judgment to surface risks, discuss trade-offs, and negotiate intake guardrails with leadership.

Preferred qualifications

  • Demonstrated track record of driving technical leverage by scaling the adoption of AI-assisted tools across a team (e.g., productizing prompt banks or integrating AI code reviews).
  • Experience building infrastructure that integrates with headless BI semantic layers (e.g., Cube.dev) and downstream AI agentic workflows (e.g., LibreChat).
  • Prior experience working with HIPAA-compliant data environments, electronic health records (EHR), or digital health operations.
  • Advanced knowledge of implementing robust RBAC frameworks, hashing, and masking strategies for sensitive clinical data.
  • Experience managing changing business processes or schema drift to gracefully adapt data models.
  • Basic Python proficiency for pipeline and tool orchestration.

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