Data Engineer (1042) - Data Enablement - DataSF, Office of City Administrator

The Data Engineer will be part of our data enablement practice, the portion of the team that helps City departments bring their data onto the platform and put it to work. This position will build and maintain production data pipelines, develop and test data models in dbt on Snowflake, and transition publishing workflows from legacy systems to the platform. The role works closely with senior engineers who provide code review and hands-on mentorship, and spends time with department analysts to understand data at its source. This is a hands-on engineering role—you don’t need years of experience, but you do need to have built things before, care deeply about data accuracy, and learn quickly.
Examples of Important and Essential Duties:
Build and maintain production data pipelines that bring department data onto the platform, complete with tests and documentation so they can be run and maintained by others.
Develop data models in dbt that transform raw department data into clean, well‑documented tables relied on by analysts across the City.
Create financial and budget data products—models built on the City’s financial and workforce systems that support migration off legacy reporting and provide departments with accurate numbers for budgeting and planning.
Support platform cost and usage reporting so the team and partner departments can understand platform expenses and how resources are used.
Help transition publishing workflows from legacy systems onto the platform, including public‑facing open data feeds.
Investigate and resolve data quality issues by tracing errors to their source, fixing problems, and adding tests to prevent future occurrences.
Support department onboarding by helping analysts understand and use the models you build.
Participate in code review and grow into reviewing others’ code as your experience increases.
Education:
An associate degree in computer science, computer engineering, information systems, or a closely related field from an accredited college or university OR its equivalent in terms of total course credits/units [i.e., at least sixty (60) semester or ninety (90) quarter credits/units with a minimum of twenty (20) semester or thirty (30) quarter credits/units in one of the fields above or a closely-related field].
Experience:
One (1) year of experience analyzing, installing, configuring, enhancing, and/or maintaining the components of a system or platform.
Substitution:
One year of additional experience as described above may be substituted for the required degree.
Completion of the 1010 Information Systems Trainee Program may be substituted for the required degree.
Note(s):
One-year full-time employment is considered equivalent to 2000 hours (2000 hours of qualifying work experience is based on a 40 hour work week). Any overtime hours that you work above forty (40) hours per week are not included in the calculation to determine full-time employment.
Applicants must meet minimum qualification requirements by the final filing date unless otherwise noted.
Every application is reviewed to ensure that you meet the minimum qualifications as listed in the job ad. Please review our articles on Employment Application and Minimum Qualifications and Verification of Experience and/or Education for considerations taken when reviewing applications.
Desirable Qualifications: The stated desirable qualifications may be used to identify job finalists at the end of the selection process when candidates are referred for hiring.
Experience building real data-moving or data-transforming projects—whether from a job, internship, or personal work—and the ability to explain how they were designed and what challenges arose.
Ability to write SQL and familiarity with at least one programming language, ideally Python; strong attention to numerical accuracy and instinct for identifying when data doesn’t look right.
Experience with financial, budget, or ERP data is a plus, as is familiarity with dbt, Snowflake, or Terraform.
Strong potential and intuition working with data, with the ability to learn new tools and the platform stack on the job.

Employment type
Full-time

Work arrangement
Hybrid