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Data Engineer Data Analyst Jobs in Hampton, VA (NOW HIRING)

Description We are seeking a Data Engineer to help us build and scale the data infrastructure that ... You will help define our technical foundation, accelerate analytics maturity, and enable teams ...

Data Engineer

Chesapeake, VA · On-site

$85K - $105K/yr

You will help define our technical foundation, accelerate analytics maturity, and enable teams ... Advocate for best practices in data management, engineering, and analytics. * Contribute to ...

Data Engineer

Chesapeake, VA · On-site

$99K - $120K/yr

We are seeking a Data Engineer to help us build and scale the data infrastructure that powers ... You will help define our technical foundation, accelerate analytics maturity, and enable teams ...

Data Analyst

Chesapeake, VA · On-site

$90K/yr

Ignite Digital is seeking a MidLevel Data Analyst to support a US Navy data analytics, cloud ... Collaborate with analysts, developers, and system engineers to design and implement datacentric ...

DATA ENGINEER

Virginia Beach, VA · On-site

$101K - $121K/yr

Data Engineer Banking (2-3 Years Experience) Company: AaraTech Inc About the Role 0AaraTech Inc is ... You will collaborate with analytics teams to support reporting and compliance needs. Ideal for ...

Palantir Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... You'll sharpen your skills in analytical exploration and data examination while you support the ...

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Showing results 1-20

Data Engineer Data Analyst information

See Hampton, VA salary details

$32.9K

$79.9K

$131.4K

How much do data engineer data analyst jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data engineer data analyst in Hampton, VA is $79,866.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,400.00 and $93,700.00 per year, depending on experience, location, and employer.

How do data engineer data analysts typically collaborate with data scientists and business stakeholders?

Data Engineer Data Analysts play a crucial role in bridging the technical and analytical needs of an organization. They work closely with data scientists by preparing, cleaning, and structuring large datasets to enable advanced analytics and modeling. Additionally, they collaborate with business stakeholders to understand data requirements, translate business questions into technical solutions, and deliver actionable insights. Effective communication and teamwork are essential, as the role often involves facilitating data access, ensuring data quality, and aligning data projects with business objectives.

What are the key skills and qualifications needed to thrive as a data engineer data analyst, and why are they important?

To thrive as a Data Engineer/Data Analyst, you need strong analytical and statistical skills, proficiency in programming languages like Python or SQL, and typically a degree in computer science, statistics, or a related field. Familiarity with data warehousing tools, ETL processes, and experience with platforms like Hadoop, Spark, or Tableau is often required. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for interpreting data and sharing insights with stakeholders. These competencies ensure accurate data management, insightful analysis, and support data-driven decision-making within organizations.

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

AspectData EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; often certifications in cloud or data toolsBachelor's or higher in CS, Statistics, or related; often advanced degrees
Work EnvironmentBuilds data pipelines, manages databases, ensures data flowAnalyzes data, creates models, interprets insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceResearch firms, tech, finance, marketing

Data Engineers focus on developing and maintaining data infrastructure, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but Data Engineers are more involved in data architecture, whereas Data Scientists focus on modeling and analysis.

Can a data analyst work as a data engineer?

A data analyst can transition to a data engineer role by developing skills in data pipeline development, database management, and programming languages like Python or SQL. While data analysts focus on data interpretation and reporting, data engineers build and maintain data infrastructure, often requiring knowledge of tools such as Apache Spark, Hadoop, or cloud platforms. Gaining experience with these technologies and earning relevant certifications can facilitate the switch between roles.

What are popular job titles related to Data Engineer Data Analyst jobs in Hampton, VA?

For Data Engineer Data Analyst jobs in Hampton, VA, the most frequently searched job titles are:

What job categories do people searching Data Engineer Data Analyst jobs in Hampton, VA look for?

The top searched job categories for Data Engineer Data Analyst jobs in Hampton, VA are:

What cities near Hampton, VA are hiring for Data Engineer Data Analyst jobs?

Cities near Hampton, VA with the most Data Engineer Data Analyst job openings:

Infographic showing various Data Engineer Data Analyst job openings in Hampton, VA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $79,866 per year, or $38.4 per hour.

$85K - $105K/yr

Full-time

Posted 24 days ago


Job description

Description

We are seeking a Data Engineer to help us build and scale the data infrastructure that powers decision making across Standard Calibrations. In this role, you will architect, implement, and maintain the systems and pipelines that transform raw data into clean, reliable, and analytics-ready datasets. You will also be working with these datasets to report on metrics for the business to base their decisions on.


You will work closely with our data, product, and engineering teams to design end-to-end data flows, integrate new data sources, and establish the foundation for long-term scalability. You will partner with stakeholders across the company - sales, finance, operations, and customer service - to ensure they have timely, trustworthy data and the tools to use it effectively.


In this role, you will directly influence how data is collected, structured, and leveraged across Standard Calibrations. You will help define our technical foundation, accelerate analytics maturity, and enable teams throughout the organization to make smarter, faster, data-driven decisions.

Requirements


Key Responsibilities:

Data Architecture & Modeling

  • Define and develop data architecture, schemas, ETL/ELT processes, and data models to develop and maintain our data pipelines and data warehouse within our Microsoft Fabric environment.
  • Ensure adherence to best practices in data modeling, scalability, governance, and performance optimization.
  • Develop standardized, well-documented semantic layers and curated datasets for analytics consumers. Ensure pipelines are resilient, observable, well-tested, and optimized for cost and performance

Infrastructure Ownership

  • Perform ongoing maintenance, tuning, optimization, and administration of SQL and Microsoft Fabric environments.
  • Monitor data pipeline and warehouse health ensuring availability, reliability, and data integrity.
  • Establish and maintain standards for version control, deployment, orchestration, and environment governance.

Cross-Functional Collaboration and Analytics

  • Partner with product teams to identify KPIs, define metrics, and develop measurement strategies. Develop and maintain Power BI data models and dashboards to visualize these metrics and provide self-service tools data analytics for the business.
  • Develop and maintain Crystal Reports alongside the business to support production needs and provide polished documents/statements for our customers.
  • Support daily, weekly, and monthly reporting needs across multiple departments.

Data Quality, Security & Governance

  • Implement and enforce data governance and security best practices, ensuring clean and lean data pipelines and datasets.
  • Troubleshoot pipeline failures, data quality issues, and system performance challenges.
  • Maintain detailed documentation for data requirements, data flows, schemas, and operational processes.

Innovation & Continuous Improvement

  • Evaluate new tools, frameworks, and architectures to enhance data engineering workflows.
  • Advocate for best practices in data management, engineering, and analytics.
  • Contribute to building a scalable, self-service analytics ecosystem that empowers teams across the organization.

Required Qualifications:

  • 5-7+ years of experience in data engineering, data analytics, or data development with a reporting focus.
  • Proficiency in Microsoft SQL, Microsoft PowerBI, and data migration tools such as Microsoft SSIS. 
  • Proficiency in designing SAP Crystal Reports 2020 or newer.
  • Experience integrating data from various sources (e.g., relational DBs, NoSQL, APIs, external SaaS platforms).
  • Ability to design scalable, maintainable, and robust data pipelines.
  • Familiarity with project management workflows and working within change management guidelines.
  • Excellent communication skills and the ability to collaborate with technical and non-technical stakeholders.
  • Must be able to pass a pre-employment drug screen.

Preferred Qualifications:

  • Experience with Microsoft Fabric or similar transformation frameworks.
  • Familiarity with cloud environments, preferably Microsoft Azure.
  • Familiarity with Visual Studio 2019 or newer.
  • Background in analytics, business intelligence, and/or reporting such as SSRS.
  • Knowledge of data governance frameworks and security best practices.
  • Experience building data products or enabling self-service analytics tools.

Safety 

It is SCI's policy to require safe operations and practices from all employees and to ensure safe working environments.


Appearance

  • Business casual

Physical Requirements

  • Ability to lift equipment weighing up to 40 pounds (with equipment, as needed)
  • Bending/squatting/kneeling/stooping/crouching
  • Able to sit or stand for long periods of time when needed
  • Ability to use and view a computer screen, keyboard, and mouse 

AAP/EEO Statement

Standard Calibrations, Inc. is committed to equal employment opportunity. We recruit, employ, train, compensate, and promote without regard to race, religion, color, national origin, age, sex, disability, protected veteran status, or any other basis protected by applicable federal, state, or local law.


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