Data Engineer - Analytics Products

Data Engineer on the DC Public Charter School Board's Analytics Products team, a remote role with a salary range of USD 83,520 - 103,172 per year, effective July 2026, responsible for building and maintaining data pipelines, data warehouse models, orchestration workflows, and Data Marts to support reporting, accountability calculations, Enterprise Intelligence, and public analytics.

Responsibilities

• Architect and sustain ETL/ELT pipelines with Airflow, SQL, and Python to power analytics, reporting products, and accountability calculations.
• Enhance PCSB data warehouse architecture, models, schemas, dependencies, and accompanying documentation.
• Support the Data Mart development and reliability, ensuring governed, non-PII data are structured for reporting using star schemas, analysis, and Enterprise Intelligence use cases.
• Create and maintain Airflow orchestration workflows for scheduled data submissions, validation, report production, and downstream analytics products.
• Implement schema validation and transformation logic to ensure submitted and processed data align with 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.

Requirements

• Minimum five years of professional experience in data engineering, analytics engineering, software engineering, database development, or related technical roles, including substantial experience using SQL and Python in production or recurring-workflow environments.
• Data ingestion and integration: Proven ability to design and maintain ETL/ELT pipelines moving data from source systems into databases, data warehouses, Data Marts, reporting layers, or analytics products; experience with structured data, handling inconsistencies, and implementing validation steps.
• Data Warehouse modeling and architecture: Experience designing or improving data models for databases, warehouses, or analytics; understanding of 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 used for reporting and analysis; familiarity with dimensional modeling, star schemas, standardized definitions, or non-PII reporting layers is a plus.
• Workflow orchestration and reliability: Experience building, maintaining, or troubleshooting scheduled data workflows using Airflow or a comparable tool; ability to monitor, diagnose, and implement durable fixes with awareness of downstream impacts.
• Database management and optimization: Proficient in writing and optimizing SQL for production data systems; knowledge of query performance, joins, indexing, migrations, data volume, and how changes affect reporting).
• Cloud infrastructure and DevOps for data: Experience with cloud data infrastructure and deployment workflows; familiarity with AWS services such as RDS, S3, IAM, CloudWatch, Lambda, ECS; experience with Git, CI/CD, Docker, and infrastructure-as-code practices is helpful.
• Data governance, quality, and security: Experience implementing data quality checks, documentation, lineage, privacy protections, access controls, or auditability within data pipelines or warehouse models; experience with education or public-sector data is helpful.
• Code quality, testing, and documentation: Ability to write maintainable, tested, and documented code with version control; comfortable with peer reviews, improving codebases, documenting assumptions, and 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, building transparent, reliable, and equitable data systems that support 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

• Comprehensive benefits plan that covers 100 percent of the employee's insurance premium.
• Generous telecommuting policy supporting remote work.
• Public Service Loan Forgiveness (PSLF) Program eligibility for government or not-for-profit employees; details at studentaid.gov.
• Compensation is non-negotiable within our system to promote fair practices.