Data Analyst Role

Peregrine Advisors LLC; Washington (District of Columbia); On-site; USD 65,000 - 95,000; Full time

Job summary

Peregrine Advisors LLC is seeking a Data Analyst to turn operational data into actionable insights in Washington, DC. You will define measures, acquire and reconcile data, and build analyses, reports, and dashboards used by stakeholders across the organization.

The role involves working with SQL, spreadsheets, and BI tools to profile, clean, and validate data, ensuring accurate guidance for decision-makers and reviewers across teams.

Qualifications

• Experience querying, cleaning, joining, aggregating, and validating data.

Responsibilities

• Create recurring reports and dashboards with measures, refresh schedules, filters, alerts, and access controls.
• Develop clean analytical datasets and semantic models reconciling source fields, business definitions, relationships, and calculation logic.
• Write queries, scripts, and repeatable workflows that replace manual reporting.
• Perform variance, trend, cohort, performance, financial, program, or operational analyses and document findings.
• Maintain data-quality checks, reconciliation reports, issue logs, and documentation that establish data provenance.

Skills

SQL

Data cleaning

Data validation

Spreadsheets

Scripting

Data visualization

Version control

Tools

BI tools

Job description

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.

Description

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.

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.

Benefits

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