Data Engineer - Analytics Products

Data Engineer on the Analytics Products team at the DC Public Charter School Board will work remotely to design and maintain data pipelines, data warehouse models, orchestration workflows, and Data Marts that support reporting, accountability calculations, Enterprise Intelligence, and public analytics. This is a remote position with an effective start date in July 2026, and a salary range of USD 83,520 to 103,172 per year.

Responsibilities

• Design, build, and sustain ETL/ELT pipelines using Airflow, SQL, and Python to support analytical workflows, reporting products, and accountability calculations.
• Maintain and improve the Data Warehouse architecture, including data models, schemas, dependencies, and documentation.
• Support the development and reliability of the Data Mart, ensuring governed, non-PII data are structured for reporting (star schemas), analysis, and Enterprise Intelligence use cases.
• Develop and manage Airflow orchestration workflows that support recurring data submissions, validation processes, report production, and downstream analytics products.
• Implement schema validation and transformation logic to ensure submitted and processed data conform to standards and Data Mart models.
• Monitor and resolve Airflow failures, pipeline errors, and data quality issues in collaboration with Analytics Engineers and Product Managers.
• Support accountability-related data infrastructure, including ASPIRE, state assessment reporting, school performance reporting, and potential concurrent accountability calculation frameworks.
• Manage cloud-based data infrastructure using AWS RDS, S3, IAM, and related services.
• Contribute to a CI/CD environment by writing tests, performing peer code reviews, and ensuring reliable deployment of data pipelines and infrastructure changes.
• Collaborate with Analytics Engineers and Product Managers to translate user stories, reporting needs, and policy requirements into reliable data models and automated workflows.
• Support Data Governance by maintaining data quality, privacy, transparency, and auditability across systems.
• Contribute to the Data Team Handbook and participate in Agile rituals, including sprint planning, reviews, and retrospectives, to improve team processes.

Requirements

• At least five years of professional experience in data engineering, analytics engineering, software engineering, database development, or a closely related technical role, with substantial SQL and Python experience in production or recurring workflows.
• Experience building and maintaining ETL/ELT pipelines that move data from source systems into databases, data warehouses, Data Marts, reporting layers, or analytics products, including handling structured data and implementing validation steps.
• Experience designing, maintaining, or improving data models for databases, warehouses, or analytics, with understanding of table grain, keys, relationships, dependencies, versioning, and downstream reporting usage.
• Experience creating governed, report-ready datasets, views, tables, or semantic models for reporting and analysis; familiarity with dimensional modeling, star schemas, and non-PII reporting is helpful.
• Experience developing, maintaining, or troubleshooting scheduled data workflows using Airflow or similar orchestration tools; ability to monitor recurring workflows, diagnose failures, and implement durable fixes.
• Experience writing and optimizing SQL for production data systems; knowledge of query performance, joins, indexing, migrations, data volume, and impacts on reporting products.
• Experience with cloud infrastructure and DevOps for data, including AWS services such as RDS, S3, IAM, CloudWatch, Lambda, or ECS; familiarity with Git, CI/CD, Docker, and infrastructure-as-code practices is helpful.
• Experience implementing data quality, privacy, lineage, documentation, access controls, or auditability in data pipelines or warehouse models; experience with education or public-sector data is helpful.
• Experience writing maintainable, tested, and documented code with version control; comfortable with peer reviews and documenting assumptions for long-term maintainability.
• Experience collaborating with analysts, product managers, program staff, or other non-engineering partners to translate reporting or accountability needs into reliable data infrastructure.
• Commitment to the DC PCSB mission, REDI principles, and building transparent, reliable, and equitable data systems for public education oversight.

Technologies

• Airflow
• SQL
• Python
• AWS RDS
• AWS S3
• AWS IAM
• AWS CloudWatch
• AWS Lambda
• AWS ECS
• Git
• CI/CD
• Docker
• Infrastructure as Code practices

Benefits

• A comprehensive benefits plan that covers 100 percent of the employee's insurance premium.
• Generous telecommuting policy.
• Public Service Loan Forgiveness (PSLF) eligibility consideration for qualifying government or not-for-profit employment; details at studentaid.gov.
• A non-negotiation policy for compensation to promote fair practices within the organization.