Analytics Engineer - U.S. Based Hybrid Opportunity

Common App is a national not-for-profit organization dedicated to the pursuit of access, equity, and integrity in the college admission process. 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. This role is central to operationalizing governance standards within enterprise systems and building the shared data foundations that power the Applied Analytics and Research team. Reporting to the Senior Director, Analytics Engineering.

Responsibilities

Evolve the shared data warehouse, semantic layer, and reusable data assets to enable scalable analytics, data governance, and artificial intelligence readiness; Operationalize governance standards within enterprise systems; Partner with Data Engineering and Applied Analytics and Research to deliver insight-ready data; Partner with Data Governance to ensure governance rules are technically enforceable within the enterprise data platform; Develop the reporting schema; Refactor existing tables and pipelines for performance, cost efficiency, and maintainability; Design and implement automated data quality frameworks; Establish monitoring and alerting for critical datasets and pipelines; Maintain warehouse data documentation; Architect data products that structure the platform for scalability, quality, and self-service

Requirements

Must live in the United States; willingness and ability to travel for periodic in-person events; Bachelor's degree in Computer Science, Information Systems, Data Engineering, Statistics, or a closely related quantitative or technical field, or 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; 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 serving multiple downstream consumers, including BI tools, analysts, and AI systems; Demonstrated thought leadership in data platform engineering; Proven ability to contribute to long-term platform planning and influence organizational data strategies; Experience implementing automated data quality frameworks, including pipeline-embedded tests, validation logic, and monitoring/alerting for production datasets; Understanding of data governance concepts and translating governance requirements (data retention, PII handling, access controls) into technical implementations; 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, including data dictionaries, lineage records, and model descriptions; Strong interpersonal and communication skills; Strong collaboration and influencing skills without formal authority; Proficiency in collaboration and version control tools (GitHub, Git)

Nice to have

Advanced training and experience in Tableau for semantic layer integration and BI dashboard development; Familiarity with data catalog and metadata management tools (e.g., Alation, Atlan, or similar); Experience working with Agile frameworks for cross-functional, product-minded collaboration; Experience in the higher education, nonprofit, or mission-driven technology sector; Relevant data engineering or cloud platform certifications (e.g., Databricks Certified Data Engineer, dbt Certified Developer, or equivalent)

Benefits

Virtual-first environment; Work-life balance; Paid Time Off (PTO); Seven company-wide holidays; Nine floating holidays; Sick leave; Monthly mental health day; Choice of PC or MAC laptop; Choice of external monitor, keyboard, mouse, and/or headset; One-time office set-up stipend; Monthly remote work stipend; Monthly mobile stipend; Market-based salaries; Performance-based bonus; 403(b) retirement plan with 5% company contribution and additional 5% company match; Choice of two health insurance plans; Health Savings Account and Medical Flexible Savings Account, depending on health plan selection; Vision insurance; Dental insurance; 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; Company provided short and long-term disability insurance; Budgeted annual funds for professional development; Growth opportunities within the company; Mutual of Omaha Employee Assistance Program; Mutual of Omaha will preparation services; Mutual of Omaha travel assistance; Pet insurance through PinPaws; 1Password family account