Data Analyst Role

About OPEN Data Jobs

OPEN Data Jobs (ODJ) is built to craft data careers. We connect high-potential data, AI, and software professionals with meaningful work on the cutting edge of the federal sector, and our aim reaches beyond any single opening: to help you understand your strengths, find the right role, and grow throughout your career.

ODJ is organized around Roles and Openings. A Role is a durable career type, such as Data Engineer or AI Engineer: it describes the work, the skills that count, and where the path can lead. An Opening is a specific position hiring right now, with a level, a location, and an application. Roles help you see where you fit; from there, there is more than one way to move.

Today, you can apply to any Opening that fits you through our secure application system. You can also register for a Role to express interest in that broader category of work. A Role registration is not an application to every future Opening.

The work

Data Analysts make operational data answerable. They work with stakeholders to define measures, acquire and reconcile data, investigate discrepancies, and turn recurring questions into analyses, reports, semantic models, and dashboards that people can use.

The daily craft combines SQL, spreadsheets, scripting, and business intelligence tools with careful domain reasoning. Data Analysts profile and clean data, define calculations, identify trends and exceptions, validate results against source systems, and present the finding in language suited to the decision.

What you'll build

· Recurring reports and dashboards with documented measures, refresh schedules, filters, alerts, and access controls.

· Clean analytical datasets and semantic models that reconcile source fields, business definitions, relationships, and calculation logic.

· Queries, scripts, and repeatable workflows that replace manual reporting and make transformations easier to test and review.

· Variance, trend, cohort, performance, financial, program, or operational analyses that identify what changed and where to investigate.

· Data-quality checks, reconciliation reports, issue logs, and documentation that establish where a number came from and whether it is fit for use.

Who you are

You are precise with numbers and curious about what sits behind them. An unexplained variance is an invitation to trace definitions, filters, timing, and source records until the result makes sense.

You can shift between a stakeholder's question and the data needed to answer it. You communicate clearly, design for the people who will use the analysis, and distinguish a useful operational conclusion from a claim the data cannot support.

What you bring

• · Practical skill in querying, cleaning, joining, aggregating, and validating data with SQL, spreadsheets, scripting, or comparable analytical tools.
• · Experience defining measures, documenting business rules, reconciling sources, and building reports or dashboards that refresh reliably.
• · Working knowledge of descriptive statistics, trend analysis, outlier investigation, data modeling, and visualization selection.
• · Habits that make analysis reproducible, including version control where appropriate, documented transformations, quality checks, and peer review.
• · The ability to present findings, assumptions, limitations, and recommended follow-up to technical and nontechnical audiences.
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Requirements

• An opening may emphasize program performance, finance, operations, audit support, product analytics, geospatial analysis, workforce data, self-service BI, or public reporting. Some openings will lean toward analytics engineering, while others will stay closer to stakeholder analysis and recurring reporting.
• Specific openings may name SQL dialects, Python or R, spreadsheet platforms, BI products, semantic-modeling languages, cloud data warehouses, statistical tools, source systems, accessibility practices, or a particular subject domain. OPEN Data Jobs will state the required technical and domain depth with each opening.