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.

About OPEN Data Jobs

OPEN Data Jobs connects AI, data, and software professionals with critical roles, primarily in the federal sector. Registering with ODJ can put your profile in view for multiple positions across several clients.

Click Apply below to register for Data Analyst Role.

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.

Compensation, benefits, work location, and employment terms are set for each specific opening and will be stated with that opening.

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