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Data Analytics Engineer Jobs in Virginia (NOW HIRING)

Highspring

Senior Consultant - Data & Analytics

Mclean, VA · On-site

$86K - $109K/yr

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 ...

Parsons

Data Analytics Architect

Alexandria, VA · On-site +1

This position collaborates with engineers, operators, analysts, and cybersecurity teams to ensure ... Data Architecture & Engineering * Design and maintain enterprise data architectures supporting UAS ...

Palnar

Data Analytics

Reston, VA · On-site

... engineering, business administration, or other related discipline. Masters degree in a related ... Data Analyst teams to develop and implement the Ab Initio solution - Develop generic solutions ...

Airbus

Data Analytics Specialist

Dulles, VA · On-site

Bachelors degree in Engineering, Computer Science, Data Science or related field * 10% Domestic and ... and analytics adoption * Fluent in English, both spoken and written * Robust coding abilities ...

Ag

Data Analytics Specialist

Dulles, VA · On-site +1

Bachelors degree in Engineering, Computer Science, Data Science or related field * 10% Domestic and ... and analytics adoption * Fluent in English, both spoken and written * Robust coding abilities ...

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All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Virginia

Data Analytics Engineer information

See Virginia salary details

$44.1K

$128.6K

$176K

How much do data analytics engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for data analytics engineer in Virginia is $128,604.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Virginia? The most popular types of Data Analytics Engineer jobs in Virginia are:
What are popular job titles related to Data Analytics Engineer jobs in Virginia? For Data Analytics Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Analytics Engineer jobs in Virginia look for? The top searched job categories for Data Analytics Engineer jobs in Virginia are:
What cities in Virginia are hiring for Data Analytics Engineer jobs? Cities in Virginia with the most Data Analytics Engineer job openings:
Data Analytics Engineer jobs near you
Infographic showing various Data Analytics Engineer job openings in Virginia as of July 2026, with employment types broken down into 1% Internship, 93% Full Time, 3% Part Time, and 3% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $128,604 per year, or $61.8 per hour.

Senior Consultant - Data & Analytics

Highspring

Mclean, VA • On-site

$86K - $109K/yr

Other

Posted 26 days ago

Job description

Transform Your Career 

We deliver unparalleled opportunities for growth and career advancement. Our dynamic, entrepreneurial culture supports your journey every step of the way. 

Embrace new challenges and deliver real value to some of the world's most influential Fortune 100 brands, growth companies transforming their industries, and mid-market firms that need help navigating the defining moments of their lifecycle. Work side by side with business leaders to solve complex client challenges and make a true impact. Love what you do as part of a diverse organization committed to collaboration and continuous learning.

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 maximize the value of their data by designing modern data platforms, building scalable pipelines, and delivering analytics and reporting solutions that enable better decision-making. Our consultants are hands-on problem solvers who partner closely with clients in fast-paced, project-based environments.

Your Impact

As a Senior Consultant, Data & Analytics, you will:

  • Design and build modern data warehouses and analytics-ready data models
  • Develop scalable, reliable data pipelines using cloud-based data platforms
  • Implement analytics, reporting, and visualization solutions that translate complex data into clear, actionable insights for client stakeholders
  • Partner with client teams to understand business objectives, data challenges, and success metrics through interviews and working sessions
  • Manage discrete project workstreams, balancing technical execution with client communication and delivery timelines
  • Present findings, recommendations, and solution designs to both technical and non-technical audiences
  • Leverage AI-assisted development environments to design, generate, test, and iterate on production-quality analytics and data engineering code
  • Support broader data transformation initiatives, including system implementations, migrations, and modernization efforts
  • Actively participate in internal knowledge sharing, mentoring, and career development activities

At a Minimum, You Will Have:

  • Bachelor's degree in Information Systems, Computer Science, Data Analytics, Engineering, or a related field
  • 2+ years of relevant experience delivering data, analytics, or data engineering solutions in a consulting or project-based environment
  • Strong proficiency in SQL and Python for data transformation, analysis, and pipeline development
  • Hands-on experience with cloud-based data platforms such as Snowflake, Databricks, Redshift, or similar technologies
  • Experience building dashboards and reports using BI tools such as Power BI, Tableau, Sigma, or equivalent
  • Experience working in AI-assisted development environments (e.g., Codex, Claude Code, Cursor) to accelerate and improve code quality
  • Demonstrated ability to manage workstreams, prioritize tasks, and deliver high-quality, client-facing solutions under tight timelines
  • Strong communication skills and comfort engaging with client stakeholders at varying levels of technical depth
  • Ability to work independently while collaborating effectively within cross-functional teams
  • Flexibility for travel, as needed

Preferably, You Will Have:

  • Experience designing data architectures and analytics solutions in cloud-native environments
  • Familiarity with modern data engineering and analytics best practices, including version control and collaborative development workflows
  • Exposure to Agile or other iterative delivery methodologies
  • Experience supporting enterprise data transformation initiatives across finance, operations, or other core business functions
  • A demonstrated interest in continuously learning new tools, platforms, and analytics techniques

Apply