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Data Systems + Analytics Manager

Job in Beaverton, Washington County, Oregon, 97078, USA
Listing for: City Fund
Full Time position
Listed on 2026-07-18
Job specializations:
  • Software Development
    Data Engineering
Salary/Wage Range or Industry Benchmark: 105000 - 145000 USD Yearly USD 105000.00 145000.00 YEAR
Job Description & How to Apply Below

WHAT WE DO

In the United States, too few students can access effective, high-performing public schools. At City Fund, we work to increase educational opportunities for students and families by partnering with city and state leaders to create innovative public school systems. We believe that public schools do best when educators have the power to make decisions that meet the diverse needs of their students, families are provided the information and access to choose the best schools for their children, and schools are held accountable for helping all students succeed.

City Fund provides financial support and expertise to local leaders seeking to improve educational opportunities in their cities. We support 24 cities across the country and hope to eventually reach most American cities. We focus on supporting:

  • High quality, innovative K-12 schools with nonprofit governing structures and diverse leadership
  • City leaders
    , including civic leaders and nonprofits that are working to build innovative public education systems and reflect the students and families they serve
  • Advocacy organizations that build the political power of families to shape education in ways that work for them
ABOUT

THE ROLE

We're looking for a hands‑on data systems & analytics manager to oversee the data infrastructure that powers our learning, evaluation, and reporting. You will steward our current data ecosystem and design and implement ongoing improvements to turn a wide range of incoming public and internal datasets into accurate, well‑modeled, reliable assets that both technical and non‑technical colleagues can rely on.

You will design and implement the transformations and semantic layer that make our Big Query warehouse usable across teams, develop and maintain the ELT/ETL pipelines that keep it current, and establish the standards and documentation that keep it trustworthy over time.

You'll also field data questions that come from across the organization and apply analytical judgment to test whether our metrics hold up.

A note on scope: our data is public, school‑level data across 40+ states with charter laws, plus internally generated programmatic, political, financial, and grantmaking datasets. We do not use PII or student‑level data at this time. Currently, our key challenge is in integrating complex, idiosyncratic data sources and ensuring longitudinal consistency. We're hiring for SQL, data‑modeling, and pipeline rigor, not streaming or big‑data infrastructure.

This role can be filled at the Manager or Senior Manager level. We care more about demonstrated capability than exact tenure—as a guide, manager‑level candidates typically bring 4+ years of relevant experience, with the senior level reflecting deeper, independent ownership of data systems and architecture (roughly 6+ years).

KEY RESPONSIBILITIES Data Infrastructure & Transformation (25%)
  • Build and maintain the central Big Query warehouse and the ELT/ETL pipelines that keep it current, versioned, and reliable.
  • Build and own the version‑controlled transformations and semantic layer (e.g., dbt or Dataform) that turn raw, idiosyncratic sources into consistent, analysis‑ready models, including aggregations by school type and geography.
  • Maintain the master list of schools City Fund tracks: apply inclusion rules, match records across vendor files, state IDs, and NCES IDs, and map each school to City Fund‑defined locations.
Data Intake, Validation & Quality (25%)
  • Coordinate external and internal data providers (vendors, consultants, partners, grantees, staff), managing their timelines, formats, and handoffs.
  • Validate and clean incoming data and build automated quality control checkpoints, including a staging‑vs‑production QC process that flags differences above set tolerances, to catch errors before they reach production.
  • Handle state‑specific rules (suppression, encodings), maintain the override/correction layer for known reporting errors, and resolve anomalies with vendors at the source.
Analytics, Reporting, & Visualization (30%)
  • Collaborate with the Strategy Team to develop custom queries and datasets for internal learning projects, organizational strategy questions, Board…
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