Data Engineer, Public Sector
As a Data Engineer for the Public Sector business unit, you will build Scale's analytical and business-intelligence infrastructure. Scale's customers process millions of tasks through our APIs, and we're looking for a talented Data Engineer to build scalable solutions to support this growth. You will have widespread purview, with responsibility for understanding, mining, aggregating, and exposing data across the entire business unit to support timely and efficient decision-making and data exploration. You will also implement Scale's data warehouse, data mart, and business intelligence reporting environments, and help users transition their workflows to these systems.
This role requires collaboration with leadership and cross-functional teams to solve complex problems and develop sustainable, scalable data solutions. Your responsibilities will include both ad-hoc analyses and the creation of core data models and pipelines, directly impacting how Scale operates and evaluates its performance.
You will:
- Work with operations, finance, and engineering to drive the development of pipelines that provide single-source-of-truth foundational accuracy
- Continually improve ongoing data pipelines and simplify self-service support for business stakeholders
- Perform regular system audits, and create data quality tests to ensure complete and accurate reporting of data/metrics
- Develop repeatable, scalable analytical solutions, such as data models, improved pipelines, or better underlying tables
- Have an active Secret security clearance (Top Secret preferred)
Ideally You’d Have:
- 2+ years of relevant work experience in a role requiring application of data modeling and analytic skills
- Ability to create extensible and scalable data schema and pipelines that lay the foundation for downstream analysis
- Mastery of SQL and relational databases; experience with programming languages (e.g., Python/R)
- Experience building a reliable transformation layer and pipelines from ambiguous business processes using tools such DBT to create a foundation for data insights
