MX
Senior Analytics Engineer
Lehi, Utah, United States · Senior
Sponsorship not specifiedDetected 1 day ago
PythonGitSQLBigQuerySnowflakeRedshiftDatabricksCI/CDMachine LearningdbtData EngineeringData ScienceStatisticsAccessibilityCollaborationProblem SolvingMentoringAdaptability
About the role
- 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.
- Establish and monitor data quality tests to ensure completeness, accuracy, and consistency.
- Ensure the right data is available to the right people at the right time, empowering self-service analytics and operational reporting.
Responsibilities
- Partner with business stakeholders, IT, and data engineering teams to define and enforce governance standards.
- Develop intuitive, business-friendly data models and assets optimized for analytics.
- Track usage metrics and continually optimize for performance and impact.
- Design, build, and maintain data pipelines and models that transform raw data into reliable, production-ready datasets.
- We build technology that helps banks, credit unions, and fintechs deliver smarter, more intuitive financial experiences to millions of people.
- We give people the space to question assumptions, design better solutions, and help shape how the company grows.
- As a trusted internal expert, you'll lead by example through mentorship, documentation, and process innovation, helping elevate data practices across the organization.
Requirements
- Bachelor's degree required, preferably in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
- 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.
Nice to have
- Proficiency with cloud data warehouses (Google BigQuery preferred
- Snowflake, Redshift, or Databricks acceptable).
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).
- Strong analytical and problem-solving skills, with keen attention to detail and system-level thinking.
- Demonstrated adaptability and perseverance in fast-paced, evolving environments.
- Track record of mentoring peers and contributing to the growth of data capabilities within an organization.
- Professional
Benefits
- Today, MX is in a phase of renewed momentum and scale, with a solid foundation and a clear vision for what's next.
- Curate and maintain high-value datasets and features in the Feature Store to support analytical and machine learning use cases.
Company info
- Our culture values curiosity, accountability, and impact.
This listing is sourced directly from MX's careers page and normalized into a canonical job model.