Senior Analytics Engineer

MX is a fintech company on a mission to empower the world to be financially strong. We build technology that helps banks, credit unions, and fintechs deliver smarter, more intuitive financial experiences to millions of people. Like many startups, we’ve navigated real growth challenges — and we’ve come out stronger on the other side. Today, MX is in a phase of renewed momentum and scale, with a solid foundation and a clear vision for what’s next. This is a place where thoughtful execution matters, innovation is encouraged, and individuals have real ownership over their work. Our culture values curiosity, accountability, and impact. We give people the space to question assumptions, design better solutions, and help shape how the company grows. If you’re looking to do meaningful work, influence outcomes, and grow alongside a company that’s ready to move fast, you’ll feel at home at MX. Job Summary As a Senior Analytics Engineer within the Operational Analytics department, you’ll play a key role in transforming complex, raw data into reliable and performant data products that power insights across MX. You’ll combine deep technical expertise in SQL, data modeling, and cloud-based data warehouses (such as Google BigQuery) with a strong sense of data stewardship, ensuring accuracy, accessibility, and trust in the analytics that drive business and product decisions. This role is ideal for a data professional who thrives at the intersection of engineering and analytics—someone who can architect and maintain scalable data models, enforce high standards for data quality, and collaborate closely with cross‑functional partners to enable data-driven decisions. As a trusted internal expert, you’ll lead by example through mentorship, documentation, and process innovation, helping elevate data practices across the organization. Responsibilities Data Stewardship: Design, build, and maintain data pipelines and models that transform raw data into reliable, production‑ready datasets. Manage and document data definitions, lineage, and transformations using GitLab or similar tools. Data Quality and Governance: Establish and monitor data quality tests to ensure completeness, accuracy, and consistency. Partner with business stakeholders, IT, and data engineering teams to define and enforce governance standards. Data Accessibility and Democratization: Develop intuitive, business‑friendly data models and assets optimized for analytics. Ensure the right data is available to the right people at the right time, empowering self‑service analytics and operational reporting. Feature Store and Data Product Development: Curate and maintain high‑value datasets and features in the Feature Store to support analytical and machine learning use cases. Track usage metrics and continually optimize for performance and impact. Collaboration and Mentorship: Partner cross‑functionally with analysts, engineers, and product teams to define data requirements, identify opportunities for process improvements, and align on strategic priorities. Provide mentorship and technical guidance to junior team members. Continuous Improvement: Stay current with emerging technologies, tools, and trends in analytics engineering, cloud computing, and data governance. Lead or contribute to initiatives that improve scalability, efficiency, and reliability of MX’s data ecosystem. Requirements Education Bachelor’s degree required, preferably in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline. Experience Minimum 5 years of experience in analytics engineering, data engineering, or business intelligence roles, with a proven track record of designing and delivering reliable, high‑performance data products at scale. Technical Skills Expert‑level SQL proficiency (including advanced window functions, CTEs, subqueries, and query optimization). Strong understanding of dimensional modeling, star/snowflake schemas, and SCD management. Proficiency with cloud data warehouses (Google BigQuery preferred; Snowflake, Redshift, or Databricks acceptable). Familiarity with programming languages such as Python for workflow automation and data quality checks. Experience with modern data versioning and collaboration tools (Git, CI/CD pipelines). Understanding of data governance, lineage, and cataloging tools (e.g., dbt, Dataform, or equivalent). Professional Skills Proven ability to collaborate cross‑functionally and communicate complex data concepts to non‑technical audiences. Strong analytical and problem‑solving skills, with keen attention to detail and system‑level thinking. Demonstrated adaptability and perseverance in fast‑paced, evolving environments. Commitment to quality, transparency, and building trust through reliable data products. Track record of mentoring peers and contributing to the growth of data capabilities within an organization. Benefits and Work Environment At MX, we are a high‑performance organization that thrives on trust and results. This role is based in Lehi, Utah. We believe in empowering our team members to deliver exceptional outcomes while taking advantage of our impressive office space when it best supports their work. Our Utah office features onsite perks such as company‑paid meals, a sports simulator, gym, mother’s lounge, and meditation room and meaningful interactions with amazing people. We encourage team members to come together in the office to collaborate, kick off key projects, or strategize cross‑functionally, fostering connection and innovation. Equal Opportunity Employer MX is proudly committed to recruiting and retaining a diverse and inclusive workforce. As an Equal Opportunity Employer, we never discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, military or veteran status, status as an individual with a disability, or other applicable legally protected characteristics. We particularly welcome applications from veterans and military spouses. All your information will be kept confidential according to EEO guidelines. You may request reasonable accommodations by sending an email to View email address on click.appcast.io. #J-18808-Ljbffr