Work on governed workforce analytics for CVS Health Workforce Insights, a technology platform used to power HR insights, Organizational Health dashboards, and future business intelligence products. You will build and operate software across Python services and automation, SQL transformations, Airflow workflows, deployment tooling, and BI integrations using Apache Superset, supporting secure, reliable reporting for workforce and people-analytics teams.
What you’ll do
- Design, implement, test, and maintain well-scoped features across Python, SQL, and workflow code, aligned to team architecture and coding standards.
- Turn product and operational requirements into technical tasks by collaborating with data engineers, analysts, and HR partners on expected behavior and acceptance criteria.
- Participate in code reviews, enhance existing implementations, and build automated tests for business logic, data contracts, and integrations.
- Develop and maintain BigQuery transformations and models, following established conventions for grain, keys, history, and query efficiency.
- Implement approved workforce metric definitions in SQL and application or BI integrations, keeping logic understandable and testable.
- Preserve metric behavior when models or interfaces change by reconciling outputs to agreed reference numbers and investigating discrepancies with metric owners.
- Document changes that affect reported numbers and obtain definition-owner approval before release.
- Contribute to Superset datasets and dashboard integrations, and support evaluation of APIs, caching, SSO, or scheduled-report behavior.
- Follow access-control requirements, including BigQuery policy-tag usage, BI row-level security, and small-cell suppression patterns.
- Keep PII out of tables, logs, and outputs where it does not belong, consulting data owners when requirements are unclear.
- Build and run security, data-quality, and regression tests with senior engineers and governance partners prior to release.
- Develop and maintain Airflow workflows, Python automation, SQL assets, and deployment-related code used by the product.
- Use the established GitHub Actions release process across dev, pdev, and prod, including environment placeholders and existing IAM/service-account controls.
- Diagnose defects using logs, tests, and system behavior; contribute fixes, monitoring, and operational documentation, and escalate production risks promptly.
- Support safe releases through review, validation, rollback, and incident processes.
- Maintain technical documentation for the components you change, including interfaces, data lineage, and operational procedures.
- Support incremental modernization of the Workforce Insights stack through refactoring, migration validation, and retirement of legacy components.
- Help maintain the team’s Apache Superset deployment by tracking upstream releases and security advisories, validating upgrades, and keeping configuration/extensions supportable.
- Prefer configuration and extension points over long-lived private forks; document necessary patches and support upstream contributions when appropriate.
- Share context and explain technical tradeoffs and metric behavior clearly to both technical and non-technical partners.
Requirements
- 3+ years of professional software development experience (or equivalent) building and supporting production software.
- 3+ years with Python (or a comparable general-purpose language), including writing readable, maintainable code and automated tests.
- 3+ years building or integrating APIs, services, data workflows, or other production systems, with the ability to reason about interfaces and failure modes.
- 3+ years working across application code, data transformations, and operational tooling as product needs require.
- 2+ years advanced SQL expertise (preferably BigQuery), including scripting, partitioning, clustering, materialized views, query optimization, and cost awareness.
- 2+ years Kimball dimensional modeling, including grain, conformed dimensions, slowly changing dimensions, bridge tables, factless facts, and fact additivity.
- 2+ years production experience with Airflow or Cloud Composer and Python for ETL, automation, data quality, and troubleshooting.
- 2+ years hands-on cloud data platform experience; GCP strongly preferred, including BigQuery, Cloud Storage, IAM, service accounts, Secret Manager, and related security concepts.
- 1+ year experience with an enterprise semantic or BI layer such as Superset, ThoughtSpot, Looker, Tableau, or Power BI, including governed metrics and row-level security.
- 1+ year experience with Git, code review, and CI/CD practices, preferably GitHub Actions across multiple environments.
- 1+ year tracing data or metric discrepancies to root cause and explaining findings to technical and non-technical audiences.
Benefits
- Medical, dental, and vision coverage
- Paid time off
- Retirement savings options
- Wellness programs
Preferred qualifications
- Experience with Python data applications, SQL transformation frameworks, Airflow, or Cloud Composer.
- Experience with BigQuery, GCP services, containerized deployments, or GitHub Actions.
- Experience with BI or semantic-layer integrations such as Superset, ThoughtSpot, Looker, or Power BI.
- HR or people-analytics knowledge, including Workday data, workforce metrics, or organizational hierarchies.
- Experience handling sensitive employee data, access controls, policy tags, or small-cell suppression.
- REST API automation; exposure to Superset on GKE, Celery, Redis, or OAuth.
- Experience maintaining open-source software used by a team, including tracking releases and vulnerabilities, planning upgrades, managing customizations, or contributing changes upstream.
- A Google Cloud Professional Data Engineer certification.
- Master’s degree in a relevant technical or analytical discipline.
Location: Sacramento, CA (onsite)
Pay range: USD 83,430 - 222,480 per year. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.
Work schedule: 40 hours per week, full time.
Education: Bachelor’s degree in Computer Science, Data Engineering, Data Science, Information Systems, or a related field, or equivalent practical experience.
Technologies you’ll use
- Python
- SQL
- BigQuery
- Apache Superset
- Airflow
- Cloud Composer
- GitHub Actions
- BigQuery policy-tag
- Superset datasets
- IAM
- Service accounts
- Secret Manager
- Cloud Storage
- Git
