Senior Analytics Engineer

Atlantic Federal Credit Union•South Portland, ME

About The Position

Are you passionate about building clean, scalable data infrastructure that power smarter decisions? Do you love transforming manual workflows into elegant, automated solutions? Atlantic Federal Credit Union is looking for a Senior Analytics Engineer to help advance our data maturity and accelerate our journey toward AI-ready, analytics-driven decision making. In this role, you’ll be a key builder behind the systems, models, and pipelines that fuel insights across the credit union. If you enjoy owning the full data engineering lifecycle—from modeling to automation to quality monitoring—and partnering with business teams who genuinely value your expertise, this is a great opportunity to make a meaningful impact. Why This Role Matters Atlantic is shifting from spreadsheets and manual reporting toward a centralized, governed, and scalable analytics ecosystem. As our Senior Analytics Engineer, you will: Build the shared data models that help all departments speak the same “data language.” Support major analytics, forecasting, and future AI initiatives across the organization. Improve data quality, reliability, and accessibility to drive faster, smarter decision-making. Your work will directly influence how the credit union understands its members, evaluates opportunities, and plans for the future. What You’ll Do

Requirements

8–10 years of related experience in analytics engineering, data engineering, BI development, or similar.
Bachelor’s degree or equivalent industry certifications.
Technical strength in SQL, data warehousing, pipeline design, and data modeling.
Experience with Microsoft’s analytics stack (or comparable tools).
Ability to work independently while influencing and supporting cross-functional teams.
A growth mindset and comfort adapting to change.

Nice To Haves

Financial services experience is a plus.

Responsibilities

Design, develop, and maintain automated data pipelines.
Build and enhance reusable datasets and semantic models for reporting and analytics.
Define and document business rules and shared metrics.
Implement data quality checks and monitoring frameworks.
Collaborate with IT and business owners to resolve data integrity issues.
Develop dashboards, reports, and analytical solutions built on centralized data models.
Translate business questions into scalable, repeatable analytic products.
Enable self-service analytics through structured, governed datasets.
Document processes, models, and standards.
Contribute to data maturity, automation, and AI-readiness efforts.
Support BI, Finance, and organizational priorities as needed.