Analytics Engineer

Role overview:

Merit America is seeking an Analytics Engineer to own the analytics platform that powers reporting, analysis, and decision-making across the organization. We're looking for someone who treats this as their platform: someone who takes responsibility for the data models, semantic layer, and reporting standards that teams rely on, and who proactively makes them more trustworthy, scalable, and easier to use rather than waiting for work to be assigned.

Our stack runs on BigQuery, dbt, Lightdash, and Fivetran. The core of the role is transforming raw source-system data into canonical models, governed metrics, and self-service reporting that teams across the organization can trust. Much of the challenge lies in the business domain itself: learner lifecycle, funnel, and outcomes definitions evolve as programs change, so judgment, curiosity, and strong communication matter as much as technical skill. We are also exploring how AI can improve how we build, maintain, and use our analytics platform, and are looking for someone who is excited to experiment thoughtfully with these tools.

This is a hands-on, individual-contributor role reporting to the Head of Data & Technology and working closely with data analysts, software engineers, and stakeholders across Program, Growth, Finance, and Operations.

Responsibilities

The responsibilities of the Analytics Engineer will include, but are not limited to, the following:

Own and improve canonical data models

Own and evolve the dbt models that transform raw source-system data into durable, reporting-ready tables.

Improve models over time by reducing duplication, clarifying grain, and documenting business logic.

Turn recurring reporting needs into reusable models rather than one-off queries.

Identify opportunities to simplify the data model and make reporting easier to understand and maintain.

Govern metrics and the semantic layer

Own the Lightdash semantic layer so core metrics are defined consistently and documented where they're used.

Maintain source-of-truth definitions, promoting and deprecating metrics as the business changes.

Improve the reporting ecosystem over time by making analytics more self-service and easier to use.

Maintain data quality and platform reliability

Build and maintain observability, testing, and monitoring across the analytics stack so data quality issues are identified early and resolved across source systems, transformations, and BI outputs.

Maintain strong development practices: version control, PR review, documentation, testing

Partner with analysts and stakeholders

Review analytics work for modeling quality and maintainability, and help analysts use the stack effectively.

Cross-train teammates so knowledge is shared rather than concentrated.

Skills and Competencies

We recognize that some individuals from underrepresented backgrounds may hesitate to apply if they don’t meet 100% of the listed qualifications.  Please don’t let that discourage you from applying! We value the unique skills, experiences, and perspectives that each applicant brings, and we encourage you to apply if you believe your background demonstrates the required skills and competencies:

Must Haves for all roles at Merit America:

Committed to Merit America’s mission to pave pathways to family-sustaining careers, break the poverty cycle, and create upward mobility for low-wage workers

Demonstrated history of embodying our values, which inform our work and drive our organization's culture

Shared sense of responsibility and ownership for our collective work in making a positive impact on the community we support, true to our value of Win & Lose Together

Committed to continuous learning and growth in advancing inclusive excellence and closing gaps across lines of difference

Passionate about fostering a workplace culture that embraces and values individual differences, aligned with our core value of inclusivity

Must Haves

Analytics engineering and data modeling

4+ years working with SQL and a modern cloud data warehouse

Strong hands-on experience with dbt

Experience building and maintaining canonical data models and governed metrics that support reporting and self-service analytics

Experience working with a semantic layer or governed BI environment (Lightdash, LookML, dbt Semantic Layer, or similar).

Strong grasp of data modeling concepts, and the judgment to work effectively in complex, evolving business domains

Comfort experimenting with AI tools as part of technical work, with strong judgment around validation, privacy, and data quality.

Ownership and collaboration

Demonstrated history of proactively improving data models, reporting systems, or governance processes without waiting for every need to be fully scoped

Strong communication with technical and non-technical stakeholders, including explaining tradeoffs and limitations clearly

Strong development discipline: version control, code review, testing, documentation

Ability to help analysts and business partners use data in sustainable, governed ways

Nice to Haves

Experience with BigQuery, Lightdash (or Looker), and Fivetran

Experience diagnosing data issues from Salesforce, LMS platforms, survey tools, or other operational systems

Experience designing and implementing data observability, monitoring, and testing frameworks (Elementary, Monte Carlo, Great Expectations, or similar)

Familiarity with Python for integrations, automation, or data investigation.

Experience with CI/CD and modern analytics engineering workflows

Experience with Terraform or other infrastructure-as-code tools

Experience in nonprofit, education, workforce development, or other mission-driven environments

Other Logistics

This position is full-time: 4-day work week (Fridays are an operating day if there is a holiday closure during the week)

Location: Remote

Salary: $152,000

Our goal is to have competitive and equitable compensation.  We have a market-based compensation approach, which means we benchmark each role from reputable data sources. We compare our benchmarks against similarly sized non-profit organizations with comparable annual budgets and geographical areas. We pay the same rate for the same roles and adjust to comply with statutory mandates.