Job Title: Data Engineer - Analytics Products

Department: Data, Operations, & Finance 

Reports to: Manager of Data Analytics Engineering

Location: Remote 

Effective Date: July 2026

ABOUT THE DC PUBLIC CHARTER SCHOOL BOARD (DC PCSB)

Every day, we’re doing the work to ensure that 44,000+ public charter school students, families, and communities receive a quality education that makes them feel valued and prepared for lifelong learning, fulfilling careers, and economic security. DC PCSB is an independent agency of the District of Columbia government. Our mission, vision, values, and work are rooted in the principle of ensuring that every DC student has access to a quality education.

ABOUT THE ROLE

The Data Engineer is a core member of DC PCSB’s **Analytics Products team**, which is responsible for building and maintaining the data infrastructure that supports agency reporting, accountability calculations, Enterprise Intelligence, and public-facing analytics products. You will design, implement, and maintain the data pipelines, warehouse models, orchestration workflows, and Data Mart structures that allow PCSB staff, school leaders, and public stakeholders to access reliable, governed, and well-documented data.

This role combines traditional data-engineering expertise — pipelines, orchestration, warehousing, and cloud infrastructure — with close collaboration across Analytics Engineers, Product Managers, and agency program teams. You will help ensure that PCSB’s data architecture supports scalability, auditability, transparency, and long-term maintainability, while maintaining compliance with PCSB’s Data Governance and REDI commitments.

Core Responsibilities

• Design, build, and maintain ETL/ELT pipelines using Airflow, SQL, and Python to support analytical workflows, reporting products, and accountability calculations.
• Maintain and improve PCSB’s Data Warehouse architecture, including data models, schemas, dependencies, and documentation.
• Support the development and reliability of the Data Mart, ensuring that governed, non-PII data are structured for reporting (star schemas), analysis, and Enterprise Intelligence use cases.
• Develop and maintain orchestration workflows in Airflow 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 PCSB 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 PCSB’s 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.

Competencies and Qualifications

Candidates should generally have at least five (5) years of professional experience in data engineering, analytics engineering, software engineering, database development, or a closely related technical role, including substantial experience using SQL and Python in a production or recurring-workflow environment.

• Data ingestion and integration: Experience building and maintaining ETL/ELT pipelines that move data from source systems into databases, data warehouses, Data Marts, reporting layers, or analytics products. This includes experience working with structured data, handling source-system inconsistencies, and implementing validation steps.
• Data Warehouse modeling and architecture: Experience designing, maintaining, or improving database, warehouse, or analytics data models. Candidates should understand table grain, keys, relationships, dependencies, versioning, and downstream reporting use cases.
• Data Mart and semantic modeling: Experience creating governed, report-ready datasets, views, tables, or semantic models that other analysts, Analytics Engineers, or business users rely on for reporting and analysis. Experience with dimensional modeling, star schemas, standardized business definitions, or non-PII reporting layers is helpful.
• Workflow orchestration and reliability: Experience developing, maintaining, or troubleshooting scheduled data workflows using Airflow or a comparable orchestration tool. Candidates should be able to monitor recurring workflows, diagnose failures, implement durable fixes, and understand downstream impacts.
• Database management and optimization: Experience writing and optimizing SQL for production data systems. Candidates should understand query performance, joins, indexing, migrations, data volume, and how database changes can affect reporting products or downstream users.
• Cloud infrastructure and DevOps for data: Experience using cloud infrastructure and deployment workflows to support data pipelines, databases, warehouses, or analytics products. Experience with AWS services such as RDS, S3, IAM, CloudWatch, Lambda, or ECS is helpful. Experience with Git, CI/CD workflows, Docker, or infrastructure-as-code practices is also helpful.
• Data governance, quality, and security: Experience implementing data-quality checks, documentation, lineage, privacy protections, access controls, or auditability practices within data pipelines or warehouse models. Experience working with education, public-sector, regulated, or high-stakes reporting data is helpful.
• Code quality, testing, and documentation: Experience writing maintainable, tested, and documented code using version control. Candidates should be comfortable participating in peer review, improving existing codebases, documenting assumptions, and supporting long-term maintainability.
• Analytics product support and collaboration: Experience working with analysts, Analytics Engineers, Product Managers, program staff, or other non-engineering partners to translate reporting, accountability, or business needs into reliable data infrastructure.
• Mission and values alignment: Commitment to DC PCSB’s mission, values, and REDI principles, including a commitment to building transparent, reliable, and equitable data systems that support public education oversight.

Compensation and Benefits
Salary is competitive and commensurate with prior experience in a similar role. DC PCSB offers a comprehensive benefits plan covering 100% of the employee’s insurance premium. If you’re employed by a government or not-for-profit organization, you might be eligible for the PSLF Program. Please visit the studentaid.gov website for eligibility details and requirements. DC PCSB offers a generous telecommuting policy.

To foster fair compensation practices within our organization, there is a non-negotiation policy built into our compensation system. The salary for this role is $83,520.00-$103,172.00.

DC PCSB is an equal-opportunity employer dedicated to fostering a unified workplace. We are committed to ensuring all employees feel valued and respected. We recognize that multiple perspectives and experiences contribute to a strong and effective team, enhancing our ability to fulfill our mission.

To Apply

Please submit a cover letter of no more than 500 words. In your cover letter, address the following prompt:

Describe a time you worked on, maintained, or improved a data pipeline, database, warehouse model, or recurring data process that other people depended on.

What was the process supposed to do? What made it important? What technical or organizational problems did you encounter? How did you diagnose the issue, improve the process, and make sure the data could be trusted? In your answer, please describe how you handled data quality, documentation, downstream users, and long-term maintainability.

We are especially interested in how you think through production data systems with real-world constraints. Strong responses will show how you balance technical implementation, reliability, governance, and the needs of the people who rely on the data.

Your response should reflect your own experience, judgment, and writing. Generic responses, responses that do not describe a specific real experience, or responses that appear to be primarily generated by an LLM or other automated writing tool will not be advanced.

The review of applications will begin immediately and will continue until the position is filled. DC PCSB is not enrolled in E-Verify and does not sponsor individuals for work visas.