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Data Analytics Developer Jobs in Virginia (NOW HIRING)

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 ...

Programming Languages: Experience with statistical programming languages such as Python (using libraries like Pandas, NumPy, and Matplotlib) or R for complex analysis and automation. Data ...

Partner with cybersecurity, engineering, product, and program management teams to align data platforms, applications, integrations, and analytics capabilities with enterprise standards. * Establish ...

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 ...

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 ...

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Data Analytics Developer information

See Virginia salary details

$24

$54

$93

How much do data analytics developer jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for data analytics developer 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 is the difference between Data Analytics Developer vs Data Analyst?

AspectData Analytics DeveloperData Analyst
Required SkillsSQL, programming, data modeling, visualization toolsExcel, SQL, basic statistics, visualization
CertificationsData analytics, programming certificationsExcel, Tableau, Power BI certifications
Work EnvironmentDevelops data tools, pipelines, and dashboardsAnalyzes data, creates reports, interprets findings
Industry UsageTech, finance, healthcare, where data tools are neededBusiness, marketing, finance, where insights are required

While both roles work with data, Data Analytics Developers focus on building data systems and tools, whereas Data Analysts interpret data to provide insights. The roles often overlap but differ mainly in technical development versus analysis and reporting.

What are some common challenges Data Analytics Developers face when integrating new data sources into existing analytics platforms?

Data Analytics Developers often encounter challenges such as data inconsistency, varying data formats, and incomplete documentation when integrating new sources. Ensuring data quality and compatibility with existing pipelines requires close coordination with data engineers and source system owners. Additionally, they must balance the need for rapid integration with maintaining data security and compliance standards. Overcoming these challenges typically involves thorough data profiling, robust ETL processes, and proactive communication across teams.

What does a Data Analytics Developer do?

A Data Analytics Developer is responsible for designing, developing, and implementing data analysis tools and solutions. They work with large datasets to extract insights, create data models, and build dashboards or reports that help organizations make data-driven decisions. Their role often involves collaborating with data scientists, business analysts, and IT teams to ensure data accuracy, performance, and security. They typically use programming languages like Python or SQL and may work with business intelligence platforms such as Tableau or Power BI.

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

To thrive as a Data Analytics Developer, you need strong analytical skills, proficiency in programming languages like Python or R, and a solid background in statistics or mathematics, typically supported by a relevant degree. Experience with data visualization tools (such as Tableau or Power BI), SQL, and cloud-based analytics platforms, as well as certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate, are highly beneficial. Excellent problem-solving abilities, attention to detail, and effective communication skills set top performers apart in this field. These skills ensure accurate data analysis, actionable insights, and successful collaboration with stakeholders to drive data-informed decision-making.
What are popular job titles related to Data Analytics Developer jobs in VA? For Data Analytics Developer jobs in VA, the most frequently searched job titles are:
Infographic showing various Data Analytics Developer job openings in Virginia as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $112,896 per year, or $54.3 per hour.

Manager, Data & Analytics

Highspring

Mclean, VA

Other

Posted 8 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.

You Are

You are a team-builder and problem-solver. You stay updated on new products and technologies. You have hands-on experience using f data, automation, and AI/ML tools and applications to creatively design, prototype, and implement solutions for your clients. You know that collaboration is key, so you look for ways to share and source best practices. If there's a new way to do something that improves outcomes for clients, you'll find it.

Your Impact

  • 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.
  • Support the shaping of the strategic direction of our growing AI/ML, automation, and Data Analytics practice.
  • Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ dashboards, data controls, data lineage, and data mapping.
  • Support data transformation initiatives across a range of service lines, including:
    • M&A Lifecycle (integrations, divestitures, and carveouts)
    • Finance Transformation
    • Enterprise Data Strategy / Governance Standup
    • Process Improvement and Automation
    • System Implementations / Migrations
    • Data and Automation Strategy and Road mapping (including how companies can leverage AI, ML, and other advanced data modeling concepts)
  • Identify insights through use of statistical, algorithmic, mining and visualization techniques.
  • Conduct interviews with client stakeholders to identify process and data challenges.
  • Document and present findings to both technical and non-technical audiences.
  • Develop analytical proof-of-concept prototypes and/ or deliver large-scale analytical platform implementations to fulfill clients' tactical and strategic requirements.
  • Develop business procedures and data management policies for ensuring data accuracy and control.
  • Create model documentation, develop implementation roadmaps, and perform knowledge transfers.

At a minimum, you will have:

  • 4+ years of data analytics, AI, ML, or GenAI experience
  • Tier 1/Tier 2 consulting or professional services firms.
  • Experience architecting and developing AI/ML solutions.
  • Experience programming in Python, SQL, and/or R.
  • Experience using GitHub (e.g., source code management).
  • Comprehensive knowledge of modern statistical learning methods.
  • Experience using applied statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasets.
  • Experience with any of the following commercial analytics, automation, and AI/ML tools: Alteryx, Power BI, Tableau, Power Automate, UiPath, Automation Anywhere, AI/ML/GenAI platforms, Informatica, Oracle EDMC, etc.
  • Proven ability to lead, motivate and build teams that deliver services and solutions that surpass client expectations.
  • Ability to lead workshops, including the gathering/documenting of requirements and use-cases and recommendation of envisioned processes.
  • Experience presenting to CXO suite.
  • Industry experience within Financial Services, Technology/SaaS, and/or Supply Chain.
  • Understanding of typical software development lifecycles (Waterfall and Agile) and their associated lifecycle artifacts.
  • Experience with identifying and correcting problems in imperfect data and processes.
  • Bachelor's degree in Mathematics, Statistics, Computer Science, Information Systems, or other technology-related field or equivalent number of years of experience
  • Flexibility to accommodate travel up to 25%.

Preferably, you will have:

  • Strong business skills and experience in accounting, corporate finance, and FP&A.
  • Familiarity with the M&A transaction lifecycle.
  • Master's degree in Information Technology, Statistics, Physics, Analytics or related field.
  • Experience managing technical development by acting as a liaison between the technical team and the user community.

The Kind of Person Who Thrives in This Role:

We are not looking for someone who fits neatly into a single box. The ideal candidate is a "bridger"-someone who can move fluidly between a technical deep dive and an executive conversation. Specifically:

  • You're a builder, not just an analyst. When you see a gap in a process or a tool, your instinct is to prototype something-a script, a template, a dashboard, not just write a slide about it.
  • You're curious about "why" and "so what." You don't just want to understand how a transformer model works; you want to understand what that means for how organizations should govern and secure it.
  • You write well. A significant portion of this role involves producing written work-reports, frameworks, articles-and clarity of writing is non-negotiable.
  • You're comfortable being the least experienced person in the room. You'll be in meetings with CIOs, CISOs, and senior partners. You need the confidence to contribute and the humility to learn.

What We Offer

  • Accelerated growth trajectory: You'll be building a practice from the ground up alongside senior leadership, gaining exposure and responsibility that would take years to earn in a larger, more established team.
  • Investment in your learning: Budget for certifications, training programs, and conference attendance.
  • Client diversity: Work across industries and with organizations at different stages of AI maturity-from Fortune 500 companies to mid-market firms navigating their first AI initiatives.