Senior Data Analyst, Strategic Operations

Role overview

You will own the architecture and buildout of Collective’s Operations Intelligence Warehouse—including the BigQuery data layer and Metabase BI—to make operational throughput, quality, variance, and capacity measurable and inspectable. You’ll also own the analytics on top of it: identifying trends early, surfacing actionable signal for leadership, and translating production telemetry into operating metrics.

You’ll join Strategic Operations, an applied operations research team that designs how the member delivery engine runs, reporting to the Head of Strategic Operations.

Responsibilities

• Architect the Operations Intelligence Warehouse
  • Lead audit, cleanup, and architecture of the Operations data subset within the shared BigQuery warehouse (source-of-truth definitions, schema/dataset design, naming conventions, documentation).
  • Manage query cost considerations.
• Set and enforce data modeling standards
  • Build and maintain dimensional models in dbt with testing, lineage, and version control.
  • Ensure every operational metric traces to a governed, documented source.
• Instrument the operation with BI and metrics
  • Design and maintain dashboards and operational health metrics, including:
    • throughput per workflow
    • cycle time
    • first-pass yield
    • exception rates
    • capacity vs demand
• Connect operations to revenue and finance
  • Join operational data with GTM and financial data to assess:
    • how service quality drives retention and NRR
    • workflow cost-to-run
    • where margin is gained or lost in the delivery pipeline
• Bring statistical rigor to daily decisions
  • Partner on statistical process control, variance analysis, and root-cause analytics.
• Raise the data practice across teams
  • Work with Data Engineering to align on SQL, modeling, and analytics engineering standards Strategic Operations scales on.

Requirements

• 5+ years of data analysis or analytics engineering at a B2B SaaS or fintech company.
• Strong experience building analytics for a human-in-the-loop service delivery operation (preferred).
• Expert-level SQL and hands-on experience with dbt (or equivalent) in a modern warehouse.
• BigQuery and Metabase strongly preferred.
• Track record leading data cleanup and/or warehouse re-architecture (untangling schemas, establishing sources of truth).
• Strong data quality instincts: testing, lineage, documentation, and git-based workflows.

Nice-to-haves / additional emphasis

• Experience with statistical process control and root-cause analytics.
• Familiarity with operational metrics such as cycle time, yield, utilization, and cost-to-serve.