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Data Analytics Jobs in Virginia (NOW HIRING)

Highspring

Senior Manager, Data & Analytics

Mclean, VA · On-site

The Team - Data & Analytics Our Data & Analytics practice is comprised of functional and technical experts across data strategy, data engineering, analytics, and transformation. We help clients ...

CGI Inc.

Data Analytics Developer, Senior

Arlington, VA · On-site

Data Analytics Developer, Senior Category: Project Management Main location: United States, Virginia, Arlington Position ID:J0925-0670 Employment Type: Full Time Position Description: CGI Federal has ...

Highspring

Senior Manager, Data & Analytics

Mclean, VA · On-site

The Team - Data & Analytics Our Data & Analytics practice is comprised of functional and technical experts across data strategy, data engineering, analytics, and transformation. We help clients ...

Acumen Solutions

Sr. Manager, Data Analytics

Mclean, VA · On-site

Acumen Solutions is looking for a Sr. Manager of Data Analytics to join our Analytics team. The Sr. Manager will work closely with the Information Management Practice Lead to help manage the team ...

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All JobsData Analytics JobsData Analytics Jobs in Virginia

Data Analytics information

See Virginia salary details

$24

$54

$93

How much do data analytics jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for data analytics in Virginia is $54.28, according to ZipRecruiter salary data. Most workers in this role earn between $43.61 and $61.49 per hour, depending on experience, location, and employer.

What job do you get with data analytics?

A career in data analytics can lead to roles such as Data Analyst, Business Analyst, Data Scientist, or Data Engineer. These positions involve analyzing data to support decision-making, often requiring skills in statistical tools, programming languages like Python or R, and data visualization software. Certifications like Certified Analytics Professional (CAP) can enhance job prospects.

Is AI replacing data analysts?

AI tools are automating certain data analysis tasks, such as data cleaning and basic reporting, but data analysts are still essential for interpreting complex data, making strategic decisions, and providing context. The role of a data analyst evolves with technology, requiring skills in programming, statistical analysis, and understanding AI capabilities, rather than being fully replaced by AI.

How does a Data Analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data specialist, or reporting analyst, focusing on collecting, processing, and analyzing data to support decision-making. They often use tools like Excel, SQL, and data visualization software, and may work in industries like finance, healthcare, marketing, or technology. Strong analytical skills and knowledge of statistical methods are essential for these positions.

What is the job of data analytics?

The job of data analytics involves examining large datasets to identify patterns, trends, and insights that support decision-making. Data analysts use tools like Excel, SQL, and visualization software to interpret data and communicate findings to stakeholders. Strong analytical skills and knowledge of statistical methods are essential for this role.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

What are the key skills and qualifications needed to thrive as a Data Analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.
What are the most commonly searched types of Data Analytics jobs in Virginia? The most popular types of Data Analytics jobs in Virginia are:
What are popular job titles related to Data Analytics jobs in Virginia? For Data Analytics jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Analytics jobs in Virginia look for? The top searched job categories for Data Analytics jobs in Virginia are:
What cities in Virginia are hiring for Data Analytics jobs? Cities in Virginia with the most Data Analytics job openings:
Data Analytics jobs near you

Pega Data Analytics Engineer

Compass Pointe Consulting

Vienna, VA • On-site

$114K - $138K/yr

Contractor

Medical, Dental, Vision, Life, Retirement

Posted 3 hours ago

Job description

Job Description
Senior Data Analytics Engineer - Pega CDH / Databricks
Position Overview
We are seeking a highly analytical and technically skilled Senior Data Analytics Engineer to support the development, implementation, and monitoring of advanced Customer Decision Hub (CDH) modeling capabilities. This role will focus on enabling faster analysis, improving data accessibility, and standardizing analytical processes across enterprise marketing and analytics teams.
The ideal candidate will have strong experience working within Databricks environments using Python/PySpark and SQL, along with expertise in large-scale data analysis, model performance monitoring, and customer interaction analytics. Experience with Pega Customer Decision Hub (Pega CDH) is strongly preferred.
This position will partner closely with analytics, modeling, marketing, and decisioning teams to create scalable analytical frameworks, reusable notebooks, and actionable monitoring solutions that improve customer engagement and model effectiveness.
Key Responsibilities
  • Develop and maintain a library of reusable queries, scripts, and analytical assets to replicate CDH customer contextual objects within external analytical platforms such as Databricks and ASL.
  • Standardize analytical processes and data retrieval methodologies for broader team usage and consistency.
  • Build scalable data pipelines and analytical frameworks using Python/PySpark and SQL.
  • Create reusable Databricks notebooks that enable self-service analytics across multiple business functions.
  • Develop standardized analytical solutions for interaction-to-outcome attribution analysis, model-to-interaction mapping, predictor performance tracking, member profile mapping, distribution analysis, arbitration analysis, and channel engagement analysis.
  • Support implementation and analysis of new model-related capabilities and features.
  • Establish baseline KPIs and monitoring frameworks for new modeling initiatives.
  • Design and support back-testing methodologies for model enhancements and propensity threshold analysis.
  • Monitor model maturity, performance trends, and operational effectiveness.
  • Develop near real-time monitoring approaches to identify low propensity scores, ineffective actions, and engagement gaps.
  • Improve visibility into model health and Next Best Interaction (NBI) program effectiveness.
  • Design analytical frameworks for eligible audience monitoring and treatment analysis.
  • Correlate interactions with demographic and behavioral data for deeper customer insights.

Required Qualifications
  • Bachelor's degree in Computer Science, Data Analytics, Information Systems, Mathematics, Statistics, or related field (or equivalent experience)
  • Strong hands-on experience with Databricks environments
  • Advanced proficiency in Python, PySpark, and SQL
  • Experience building reusable analytical frameworks and notebooks
  • Experience performing large-scale data analysis and data modeling
  • Strong understanding of model performance monitoring and KPI development
  • Ability to translate business questions into scalable analytical solutions

Preferred Qualifications
  • Experience with Pega Customer Decision Hub (Pega CDH)
  • Experience supporting marketing analytics, customer engagement, or decisioning platforms
  • Familiarity with propensity models, arbitration logic, and customer interaction analytics
  • Experience with monitoring frameworks and real-time analytical alerting
  • Understanding of customer journey analytics and Next Best Action/Interaction programs
  • Experience working in enterprise analytics or customer intelligence environments

Key Skills
Databricks, Python, PySpark, SQL, Data Engineering, Data Analytics, Model Monitoring, KPI Development, Customer Analytics, Predictive Modeling, Marketing Analytics, Notebook Development, Data Standardization, Decisioning Analytics, Stakeholder Collaboration
Success Metrics
  • Creation of reusable and scalable analytical assets for enterprise use
  • Reduction in time required to conduct CDH and model analysis
  • Improved visibility into model health and customer engagement effectiveness
  • Increased consistency and repeatability of analytical processes
  • Enhanced ability for teams to perform self-service analytics and monitoring

We offer Medical, Dental, Vision, Basic Life, Short-Term Disability, Accident, Term Life, Whole Life, and 401k for all W2 Consultants. A benefit overview will be provided as requested.

Apply