Analytics Engineer

Analytics Engineer
Remote | Product and Development | Full-Time WHO WE ARE

Headquartered in Nashville, Tenn., Ncontracts leads the industry in integrated risk management and compliance solutions, serving over 5,000 financial institutions nationwide. As a seven-time Inc. 5000 Fastest Growing Companies honoree and consistent year-over-year recipient of "Best Places to Work" awards, we offer a thriving, work environment where career growth and life-work balance go hand in hand.

At Ncontracts, you’ll join a team of industry experts dedicated to strengthening the financial services sector through innovation and thought leadership. We’re seeking creative, collaborative, and self-driven professionals across all areas of our business - from developing cutting-edge solutions to sales, marketing, customer support, and beyond. Join us in our mission to make the financial industry stronger and more resilient, while advancing your career in a supportive, dynamic environment that values your unique skills and perspectives.

We are currently seeking an Analytics Engineer to join our growing team! The Analytics Engineer reports to theData Architectandis responsible for building the data models and analytical frameworks that drive product improvement across

Ncontracts’ suite of risk management and compliance solutions.

This role sits at the intersection of data modeling and product analytics. You’ll own the transformation and presentation layers that turn raw product data into actionable insights, working closely with engineering and product teams to identify what’s working, what isn’t, and why. You’ll need strong SQL and modeling skills to build reliable, well-tested datasets, and equally strong product intuition to know which metrics actually matter for our financial institution customers.

Our modern data stack includes Snowflake as our cloud data warehouse, dbt for data transformation and modeling, and Sigma for business intelligence and visualization. You’ll own the modeling layer end-to-end—designing well-structured, documented, and tested datasets that power decisions across the organization.

This role will have a direct impact on our customers and our brand. You’ll deliver the next generation of customer-facing reporting, dashboards, and data products that elevate the Ncontracts experience and set a new standard for how financial institutions interact with their data.

We’re looking for candidates who are curious, resourceful, and genuinely excited about AI—whether that’s using it to streamline their own workflows, finding smarter ways to validate data, or simply staying on top of how the landscape is evolving. You don’t need to be an ML engineer, but we want someone who leans into new tools and approaches rather than waiting to be told to use them.

• Design, build, and maintain the data models in Snowflake using dbt that power product analytics—from raw source data through to business-ready, well-documented datasets
• Define and maintain metrics frameworks and KPIs that drive product and business decisions across the organization
• Build interactive dashboards and self-service reports in Sigma that empower stakeholders to explore data and answer their own questions
• Design instrumentation strategies with engineering teams to ensure we’re capturing the right signals from Ncontracts’ product suite
• Partner with product managers to translate fuzzy questions (“why is this feature underperforming?”) into precise, answerable analyses
• Conduct deep-dive analyses including funnel analysis, cohort analysis, and root cause investigations to surface product insights
• Own data quality end-to-end, including dbt tests, validation, documentation, and monitoring across all models
• Optimize query performance and warehouse costs in Snowflake through efficient modeling patterns, materialization strategies, and resource monitoring
• Establish and enforce data governance standards, including naming conventions, documentation requirements, and consistent metric definitions to maintain a single source of truth
• Contribute to the evolution of the data platform by evaluating new tools, technologies, and best practices