Senior Analytics Engineer (Finance & Operations)

Skylight is a technology startup building products and services designed to improve family life. The Senior Analytics Engineer will own the Finance and Operations data layer, integrate data from systems such as NetSuite, Ramp, and Pigment, and build trusted models, metrics, and dashboards for leadership decision-making.

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

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
• Experience with source-of-truth systems such as ERP (NetSuite), WMS, TMS (OSCA), or CPM (Pigment)
• Experience with wholesalers and EDI