Data Engineer

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Skimmer

11 - 50 employees

☁️ SaaS

🤝 B2B

⚡ Productivity

SaaS • B2B • Productivity

Skimmer is a prominent pool service management software platform that aims to streamline operations for pool service businesses. It offers an all-in-one solution that allows service providers to get organized, grow their business, and manage reputation through features like technician scheduling, customer data organization, and automated billing. Skimmer's user-friendly apps provide real-time visibility and efficiency improvements, helping technicians reduce paperwork and drive time, while also enhancing customer communication. Trusted by over 30,000 pool pros in North America, it features robust support and resources for businesses at any stage of growth, from just getting started to owning the market.

📋 Description

• Build and maintain the data models and transformations that power reporting in the Skimmer product, leveraging tools like Fivetran transformations, dbt, and Sigma Computing materializations • Build and maintain customer-facing data models and reports in Sigma Computing, embedded within the Skimmer application • Manage and extend ingestion using Fivetran across a growing set of sources • Develop and maintain data transformations in Python and SQL against our Snowflake data warehouse • Partner with product and engineering to turn customer needs into reliable, performant reporting experiences • Collaborate with application engineers to understand source systems and ensure clean, reliable data capture • Monitor data quality, reliability, and report performance, and troubleshoot issues as they arise • Document data models, definitions, and architecture to support a growing team

🎯 Requirements

• Disciplined Problem-Solving: Proven ability to decompose complex business problems into structured, executable plans. You prioritize understanding the 'why' and 'how' of data before implementation. • Proactive Communication: Comfortable identifying ambiguity and proactively seeking clarity from stakeholders rather than making assumptions. • Ownership of Quality: A strong sense of ownership—you don't consider a task 'done' until it is validated, performant, and meets the documented requirements. • Demonstrated experience in data engineering, with a track record of owning data infrastructure end to end • Strong SQL skills and hands-on experience with a cloud data warehouse (Snowflake preferred) • Proficiency in Python for data transformation and automation • Experience working with C#/.NET application environments and partnering with application engineers on source systems • Experience with managed ingestion and transformation tooling (Fivetran, dbt, or similar) • Hands-on experience building data models and reports in a BI/analytics platform (Sigma Computing a strong plus), ideally embedded in a customer-facing product • Proficiency with AI coding tools like Claude or Cursor to work efficiently and raise your output • Solid understanding of data modeling concepts and ELT/ETL best practices • Strong communication skills and comfort working with both technical and non-technical partners • Nice to Have: Experience with embedded analytics or customer-facing reporting at scale • Experience building data products in a SaaS or product-led company • Experience with rigorous code review processes and contributing to maintaining high engineering standards within a team.

🏖️ Benefits

• Competitive base pay + bonus potential • Generous medical, dental, and vision plans (we pay 100% of your premium and 50% of your dependents’) • Fantastic culture with a very strong eNPS- we work hard, celebrate wins, and learn as we go to always be improving to benefit our customers. • Immediate access to 401(k) with company match • Flexible PTO (MINIMUM of 10 days required every year) • 12 weeks paid parental leave for birthing parent, 6 weeks paid leave for supporting partner • Remote work friendly • Comprehensive learning and development budget • A manager dedicated to your development

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