Analytics Engineer – U.S. Based Remote Opportunity

Role Overview

The Analytics Engineer is the technical architect responsible for evolving Common App’s shared data warehouse, semantic layer, and reusable data assets to enable scalable analytics, data governance, and artificial intelligence readiness across the organization.

What You Will Do

Developing Common App’s reporting schema, refactoring existing tables and pipelines for performance, cost efficiency, and maintainability; designing and implementing automated data quality frameworks; establishing monitoring and alerting for critical datasets and pipelines; maintaining warehouse data documentation; and architecting data products that structure the platform for scalability, quality, and self-service.

Why It Might Be a Fit

The ideal candidate will possess advanced training and experience in Tableau for semantic layer integration and BI dashboard development, familiarity with data catalog and metadata management tools, and experience working with Agile frameworks for cross-functional, product-minded collaboration.

Requirements

• Candidates must live in the United States.
• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Statistics, or a closely related quantitative or technical field; or an equivalent combination of education and experience.
• 5-8 years of progressive experience in analytics engineering, data engineering, or a closely related data platform role.
• Demonstrated experience working within an enterprise data warehouse environment at scale, including ownership of data models, transformation pipelines, and data quality processes.
• Experience implementing data governance requirements — such as retention, deletion, or PII controls — within a production data platform.
• Strong expertise in SQL and data modeling, including dimensional modeling, star/snowflake schemas, and modern data transformation approaches.
• Demonstrated experience designing, building, and maintaining data pipelines and transformation layers within cloud data warehouse platforms (e.g., Databricks, Snowflake, BigQuery, or equivalent).
• Experience with Databricks-specific features, including Unity Catalog, Delta Live Tables, or Databricks workflows.
• Experience designing and maintaining a semantic layer or metrics layer that serves multiple downstream consumers, including BI tools, analysts, and AI systems.
• Demonstrated thought leadership in data platform engineering, with a track record of innovating and contributing to the advancement of analytics engineering practices within or beyond the organization.
• Proven ability to contribute to long-term platform planning and influence organizational data strategies through technical expertise and cross-functional engagement.
• Demonstrated experience implementing automated data quality frameworks, including pipeline-embedded tests, validation logic, and monitoring/alerting for production datasets.
• Understanding of data governance concepts and experience translating governance requirements – including data retention, PII handling, and access controls – into technical implementations within data platforms.
• Proficiency in Python for data engineering and analytics workloads; familiarity with orchestration tools (e.g., Apache Airflow, dbt Cloud, or Databricks AI/BI).
• Experience designing and implementing data products and reusable data assets for self-service analytic consumption.
• Strong documentation practices, with the ability to create and maintain clear, accurate data dictionaries, lineage records, and model descriptions.
• Strong interpersonal and communication skills, with the ability to collaborate effectively with analysts, researchers, data scientists, and governance stakeholders of varying technical backgrounds.
• Strong collaboration and influencing skills, with the ability to build trusted relationships with stakeholders across technical and non-technical functions and drive outcomes without formal authority.
• Proficiency in collaboration and version control tools (GitHub, Git).

Benefits

• Work-Life balance
• Virtual-first office
• Paid Time Off (PTO)
• Seven company-wide holidays
• Nine floating holidays
• Sick leave
• Monthly mental health day
• Virtual-first support
• Choice of PC of MAC laptop
• May choose an external monitor, keyboard, mouse, and/or headset
• One-time office set-up stipend
• Monthly remote work stipend
• Monthly mobile stipend
• Financial security
• Market-based salaries
• Performance-based bonus
• 403(b) retirement plan
• 5% company contribution
• additional 5% company match
• 3-year vesting schedule
• Participation may begin immediately
• Health & wellness
• Choice of two health insurance plans
• Health Savings Account, depending on health plan selection
• Medical Flexible Savings Account, depending on health plan selection
• Vision insurance
• Dental insurance
• Insurance coverage begins on the date of hire
• Dependent Care Flexible Spending Account
• Maven virtual clinic for women’s and family health
• Company provided life and ad&d insurance
• Opportunity to purchase additional life insurance for self, spouse, and dependents
• Company provided short and long-term disability insurance
• Career development
• Budgeted annual funds for professional development
• Growth opportunities within the company
• Additional perks
• Mutual of Omaha Employee Assistance Program
• Mutual of Omaha will preparation services
• Mutual of Omaha travel assistance
• Payroll dedication pet insurance through PinPaws
• 1Password family account

Tagged as: BigQuery, Python, Snowflake, SQL, Tableau