Senior Analytics Engineer, Skylight

• 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

Desirable

• Skylight is a technology startup building the OS of the family. We make Skylight Calendar, the smart calendar loved by millions of families
• Our mission is to connect loved ones by creating the world’s simplest products and services that improve family life
• Our founders are former venture capitalists and serial entrepreneurs who have scaled this business to $300M+ in annual revenue while being completely bootstrapped and profitable. We get to grow a happy, healthy company focused on making products our customers love without investors breathing down our necks
• We are expanding our Data team and are in need of a rigorous Senior Analytics Engineer to partner closely with our Finance and Operations teams
• This role will own the Finance/Operations data layer, bring new data into our warehouse from systems like NetSuite, Ramp, and Pigment, and build the dashboards and metrics leadership relies on to run the business
• 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