Analytics Engineer

Merit America

Analytics Engineer owning and improving data models for reporting and decision-making at Merit America. Collaborating with data analysts and stakeholders to create self-service analytics.

Posted 7/7/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $152,000 per yearWebsite

Tech Stack

Tools & technologies

CloudSQL

About the role

Key responsibilities & impact

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.
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.
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
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.

Requirements

What you’ll need

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.
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

Benefits

Comp & perks

Medical, Dental and Vision insurance (100% Paid Employee Only Coverage)
Flexible Spending Account and Health Savings Account
Dependent care Flexible Spending Account
Health Reimbursement Account fully funded by Merit
Education & personal development reimbursement
Catalog of courses for professional learning and development
Short and long-term disability
Unlimited vacation (after a 90-day introductory period)
Paid Parental Leave and Adoption benefits (after 1 year of employment)
11 federally recognized holidays
2 week holiday office closure in December/January
401(k) retirement plan with automatic Merit contribution
Wellness Benefits/Wellness Resources
Discount perks at work program
Phone/technology stipend
Home office setup stipend
Affinity groups and community building via virtual, in-person, and/or regional meetups

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLDbtData ModelingAnalytics GovernanceData Quality AssuranceVersion ControlTestingDocumentationReporting Systems ImprovementSemantic Layer Management

Soft Skills

Strong CommunicationCollaborationProactive Problem SolvingCross-TrainingStakeholder Engagement