Data Analytics Engineer, SaaS Analytics Solution (data warehouse + adv SQL exp. req.)
Location: Washington, DC 
Salary: $150,000 - $225,000 (DOE) + Bonus + Benefits
Benefits: Health Insurance, 401k plan, PTO, Paid Holidays
Job Type: Full-Time | Hybrid – In Office 2x/week
Typical Hours: Monday-Friday, 40 hours/week
Start Date: ASAP
Sponsorship is not available

Data Analytics Engineer, SaaS Analytics Solution Description

Our client is a fast-growing SaaS company in the FinTech space, providing cutting-edge solutions. Led by seasoned executives behind platforms like Workday and Zuora, the company offers a high-impact, product-led environment at the intersection of finance and technology. They are seeking a hands-on Data Analytics Engineer to join their team in Washington, DC. The ideal candidate brings hands-on, end-to-end development experience in data analytics or reporting solutions, as well as expertise in data warehouses (ex. Snowflake or similar) and BI visualization tools (ex. Google Looker or similar), with a strong command of complex SQL and data architecture. In this role, you will build and optimize the company’s analytics infrastructure – designing robust data pipelines, crafting advanced SQL transformations, and developing scalable interactive dashboards that deliver real-time insights. If you thrive in fast-paced startup environments and are passionate about building clean, efficient data systems from the ground up, this is a unique opportunity to take ownership of the reporting stack and shape the future of analytics at a modern FinTech SaaS company.

Data Analytics Engineer, SaaS Analytics Solution Responsibilities

•    Architect and build scalable data pipelines and analytics
•    Develop and manage data warehouses, with an emphasis on Snowflake
•    Create and maintain data models and dynamic dashboards in Looker
•    Write and maintain complex SQL queries for large, real-time datasets
•    Develop scalable ELT pipelines using Python
•    Create dashboards and visualizations that provide business insights
•    Integrate data from multiple sources and ensure consistency and performance
•    Continuously improve data accessibility, performance, and reliability
•    Partner cross-functionally to define KPIs and BI architecture
•    Document system design, data flows, and integration points 
•    Collaborate on the future roadmap for analytics platforms

Data Analytics Engineer, SaaS Analytics Solution Qualifications

•    5+ years of end-to-end data analytics solution development experience required
•    5+ years of data warehouse (e.g. Snowflake, Click House, Redshift, etc.) experience required
•    5+ years of advanced SQL (joins, window functions, CTEs, subqueries) experience required
•    5+ years of Python for analytics, automation, and pipeline development experience required
•    Familiar with event-based data (e.g. Segment, Amplitude) and real-time pipelines required
•    Experience in a start-up environment required