Analytics Engineer

THE ORGANIZATION

The Charter School Growth Fund (CSGF) is a leading nonprofit venture philanthropy fund that has spent 20+ years identifying high-quality public charter schools and investing in their growth. Today the portfolio spans 200+ networks, 1,700+ schools, and more than 840,000 students.

This role sits within a new public data infrastructure project that CSGF is incubating alongside its core operations. The project is designed to evolve our internal assessment data pipeline into free, open infrastructure that researchers, funders, policymakers, and school networks can use independently. School performance data is currently fragmented across dozens of state agencies, inconsistently formatted, and practically inaccessible to anyone without significant technical resources. This platform processes standardized assessment data across 40+ charter states, calculates school performance metrics, and publishes results through a public-facing portal. A core part of our vision is building toward an open source codebase and we're looking for someone who is excited about that kind of ultimate public-facing technical work, not just internal tooling.

THE OPPORTUNITY

About Our Team

This role sits within a small, dedicated team building public data infrastructure for the education investing,  research, and policy community. The team operates as a focused engineering and data function: processing state assessment files, maintaining the data pipeline, publishing metrics, and keeping the platform and its documentation current. Everyone on the team works close to the data and close to the code.

The team is organized around four core functions:     Data Collection and Management   Infrastructure and Engineering   Data Validation and QA   Publishing and Documentation

Our Analytics Stack     DuckDB + dbt (data modeling)   Python (metrics and validation)   Quarto (portal and documentation)

About This Role

As an Analytics Engineer you will help build and maintain the data models, validation scripts, and documentation that the platform depends on. This is a one-year contract role with the possibility of extension. This role will report to the Vice President who owns product direction and architecture. The team is highly collaborative and there are always opportunities to develop skills outside the core responsibilities of an individual role.

The project runs on an annual state release cycle, with the bulk of new assessment data arriving in the summer months. This role will need to be actively contributing to parser updates and dbt model changes within the first four to six weeks of starting. We are looking for someone who can orient in an unfamiliar codebase quickly and move from observation to independent contribution without an extended onboarding period.

KEY RESPONSIBILITIES

Below is a general outline of responsibilities. Roles and responsibilities may evolve to meet the needs of the project.

Data Modeling and Transformation

• Build and maintain dbt models that transform raw state assessment files into clean, analysis-ready datasets
• Develop new state parsers for assessment files that vary significantly in format, structure, and quality across states. This requires independent problem solving, not just following established patterns.
• Contribute to school and CMO classification reference datasets, keeping them accurate as the underlying data evolves

Data Quality, Testing, and Documentation

• Write dbt tests and maintain data documentation so that outputs are auditable by external researchers
• Perform in-depth QA on state data, identifying and resolving issues across heterogeneous source formats
• Author data dictionaries and methodology documentation with the same care as the code itself

Data Validation and Portal Publishing

• Use Python to perform rigorous QA and data validation: cross-state consistency checks, metric range validation, outlier detection, and regression testing against prior releases
• Write validation scripts that can be re-run as data updates, creating a consistent and reviewable QA record
• Publish documentation, data dictionaries, and methodology updates to the Quarto-based portal as part of regular data releases. The portal structure exists; this role maintains and extends its content.
• Write clearly for a mixed audience: technical enough for researchers building on the data, accessible enough for non-technical partners tracking what changed and why

REQUIRED QUALIFICATIONS

Expected Skills and Characteristics

• Hands-on experience writing and maintaining dbt models in a production or near-production environment
• Solid SQL skills, including the ability to debug complex transformations and identify data quality issues
• Comfort working with messy, real-world data: inconsistent formats, missing values, undocumented quirks, and files that require investigation before they can be modeled
• Comfort with Python for data analysis tasks: reading files, transforming data, writing validation scripts
• Ability to work independently on loosely defined problems. New state parsers and unfamiliar file formats are a recurring part of this role, not an exception.
• Familiarity with software development practices: version control with Git, code review, and basic CI/CD workflows
• Strong written communication skills: able to document data decisions, methodology choices, and known limitations clearly for a non-technical audience
• Strong attention to detail and a habit of verifying outputs rather than assuming correctness

Nice to Have

• Familiarity with DuckDB or other embedded/local analytics databases
• Familiarity with Quarto or Markdown for publishing data outputs
• Experience contributing to open-source projects or building for public data audiences
• Comfort using AI coding tools (Claude Code, Cursor, Copilot, or similar) as part of a day-to-day development workflow
• A general orientation toward AI-augmented development: using LLMs routinely across code review, documentation, debugging, and exploratory analysis

Educational Background and Work Experience

• Experience as an analytics engineer, data analyst, data engineer, or similar role; or relevant undergraduate education (e.g. B.A. in Computer Science, Data Science, or a related field)
• Background in education data, public sector data, or policy-adjacent research contexts is a plus

COMPENSATION 

Compensation is commensurate with experience and education. The target salary range for this role is $75,000-$85,000 annually. CSGF offers a very competitive package of benefits, including: health, life, disability, and dental insurance coverage; vacation/holidays and parental leave; and participation in CSGF’s 403(b) plan. Candidates must have permanent authorization to work in the US.

START DATE

CSGF is seeking candidates who can start as soon as possible.

WORKING AT CSGF

We are focused on hiring and developing great people and believe that building diverse perspectives across our team makes us more effective in expanding our impact. (This is reflected in Our Commitment Statement.) Our core values are:

Results

• We believe that student success is the ultimate measure of our performance.
• We work with urgency and intentionality for the portfolio and their schools. 
• We hold ourselves accountable to strong outcomes.
• We relentlessly prioritize our resources to drive positive, measurable, attributable impact for the charter leaders, their schools, and ultimately students.
• We believe strong results come from good decisions, and the best decisions are made when we use data - both quantitative and qualitative - and gather input from diverse perspectives, especially those most impacted by the work.  
• We celebrate our wins and learn from our losses.

Teamwork

• We value organization over team, and we value team over individual.
• We actively break down silos and collaborate across teams.
• We believe building strong, healthy relationships is critical to move our work forward.
• We seek to proactively communicate across teams to strengthen our outcomes and add value for the portfolio.

Integrity

• We believe that trust is our most important asset, and we must earn and maintain the trust of the portfolio member leaders, investors, and our team to achieve our goals.
• We are often entrusted with sensitive and confidential information about the portfolio - we do not ever violate these confidences.
• We show ownership for our successes and our failures. 
• We speak directly to the person, even when it's messy and hard, and get ahead of potential problems.
• We do the right thing, even when no one is watching.

Respect 

• We understand and acknowledge our place in the value chain – the students, teachers, principals and other leaders at portfolio networks are doing the hardest, direct and most impactful work in their schools each day.
• We prioritize humility and embrace getting better every day.
• We are curious and open-minded.
• We are aware of our own biases and how they might affect our judgment, and we take ownership to mitigate their impact.

Entrepreneurship

• We take calculated risks, looking for new ways to add value and improve how we work.
• We are problem solvers in all aspects of our work.
• We actively connect people and ideas in strategic ways to foster new ideas and learning. 
• We acknowledge not all investments will succeed and embrace failure as it facilitates deeper learning for our organization and the portfolio.

E-VERIFY STATEMENT

This employer participates in E-Verify and will provide the federal government with your form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work in the, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you. Including terminating employment. Employers can only use E-Verify once you have accepted a job offer and completed the I-9 form.

Charter School Growth Fund provides equal employment opportunity for all applicants and employees.