RESEARCH DATA SPECIALIST II

About the role

The Research Bureau is seeking a Research Data Specialist II, also known as a Research Data Engineer. This position is a lead data engineer responsible for building efficient pipelines that underpin in-house research and analytics that inform decision-making and improve service delivery across CDSS programs.

Responsibilities

• Operate with minimal oversight on complex, high-stakes projects, linking administrative records across systems
• BUILD reproducible data pipelines
• DESIGN complex database structures
• DEVELOP automated workflows that help operationalize research findings
• ENSURE the quality and security of sensitive program data
• USE data to INFORM actions that improve program delivery and outcomes for the people CDSS serves
• PRIMARY emphasis on data engineering in the service of research and public impact
• BRING working knowledge of causal research methods (experimental design, quasi-experimental techniques, or program evaluation)

Requirements

The primary emphasis of this role will be data engineering in the service of research and public impact. However, candidates should also bring working knowledge of causal research methods (experimental design, quasi-experimental techniques, or program evaluation) to understand what the data infrastructure must support and contribute to evaluation work when needed.

Qualifications

To be considered for this position, applicants must describe a project they led or co-led that required them to both engineer data systems or pipelines and apply quantitative or causal methods to support research, program operations, or decision-making. The response should address: what research question(s) or policy decision(s) the work aimed to support, and what was at stake; the data sources involved — including their scale, complexity, and any challenges in linking, transforming, or preparing them; the tools and technologies used (e.g., SQL, Python, R, cloud platforms, version control, orchestration tools); the statistical or causal inference methods applied and why they were appropriate given the data and question; and how the work was ultimately used to inform decisions or improve outcomes.

Skills

Applicants should bring working knowledge of causal research methods (experimental design, quasi-experimental techniques, or program evaluation) to understand what the data infrastructure must support and contribute to evaluation work when needed.

Benefits

N/A

Pay

$7,640.00 - $9,561.00

Schedule

Hybrid