Senior Analytics Engineer (Finance & Operations)

Requirements

• Experience: 5+ years in an analytics role with exposure to financial or operational data sets.
• Technical Skills: Strong SQL skills and experience building reusable, well-structured data models in a cloud data warehouse environment, ideally Snowflake; experience with BI or semantic-layer tools such as Omni, Looker, Tableau, Power BI, or Sigma.
• Data Quality Mindset: Experience validating outputs, reconciling discrepancies, documenting assumptions, and creating checks for critical metrics.
• Business Acumen: Ability to understand business processes and translate them into data models, metrics, dashboards, and documentation.
• Communication: Strong stakeholder management skills, including gathering requirements, managing expectations, pushing back constructively, and communicating tradeoffs.
• Adaptability: Comfort working in an early-stage or evolving data environment where systems, pipelines, definitions, and ownership boundaries may still be forming.
• Preferred:
• Experience with source-of-truth systems such as ERP (NetSuite), WMS, TMS (OSCA), or CPM (Pigment).
• Experience with wholesalers and EDI.
• -
• 5+ years in an analytics role with exposure to financial or operational data sets.
• Strong SQL skills and experience building reusable, well-structured data models in a cloud data warehouse environment, ideally Snowflake; experience with BI or semantic-layer tools such as Omni, Looker, Tableau, Power BI, or Sigma.

Benefits

• Our competitive compensation package includes:
• Competitive Salary + Equity Package
• 401K matching
• Wellness, learning, and home-office budgets
• Health, Dental & Vision Medical Plans
• Tremendous autonomy to set the direction of your work
• Unlimited PTO
• Company holidays on the first Friday of every month (Excluding November, December, and January)

Equal opportunity employer

Responsibilities

• Stakeholder Collaboration: Partner with Finance, Operations, and the rest of the Data team to understand business processes and source-system workflows, define pipeline requirements, and identify data gaps and downstream reporting impacts.
• Data Infrastructure: Own the Finance and Operations data layer and build trusted, reusable data models that support reporting, analysis, and decision-making.
• Data Integration: Design and document how data should flow between source systems such as NetSuite, Ramp, and Pigment into Snowflake and Omni.
• Data Quality: Create validation checks, reconciliation workflows, and exception reporting to improve trust in critical Finance/Ops data across source systems, Snowflake, and Omni.
• Metric Governance: Define and govern key Finance/Operations metrics with business owners, including business logic, data grain, source of truth, ownership, refresh cadence, and known limitations.
• Dashboard Development: Create and maintain dashboards, from executive-level summaries to granular self-serve analytics, to communicate performance metrics and support root-cause analysis.
• Continuous Improvement: Identify and execute opportunities to automate manual data flows, reporting processes, and reconciliation workflows.
• Strategy: Be a strategic partner with our Finance & Ops teams, collaborating with them to build and improve metrics such as LTV/CAC, Cost Per Unit for Last Mile, etc.