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Enterprise Data Engineer Jobs (NOW HIRING)

GRVTY

Enterprise Data Engineer

Chantilly, VA

$117K - $140K/yr

The successful Enterprise Data Engineer must be a skilled and detail-oriented professional with expertise in utilizing Python, SQL, and Palantir (or other ETL platforms) to extract, transform, and ...

Bespoke Technologies, Inc

Enterprise Data Engineer

Herndon, VA · On-site

$117K - $141K/yr

BT-334 - Enterprise Data Engineer Skill Level: Mid-SME Herndon, VA (fully on-site, no remote option) **Please do NOT apply if you do not have an active Poly clearance. Those without a Poly will not ...

GRVTY

Enterprise Data Engineer

Chantilly, VA · On-site

$150K - $200K/yr

The successful Enterprise Data Engineer must be a skilled and detail-oriented professional with expertise in utilizing Python, SQL, and Palantir (or other ETL platforms) to extract, transform, and ...

GRVTY

Enterprise Data Engineer

Chantilly, VA

$150K - $200K/yr

The successful Enterprise Data Engineer must be a skilled and detail-oriented professional with expertise in utilizing Python, SQL, and Palantir (or other ETL platforms) to extract, transform, and ...

The Josef Group

Enterprise Data Engineer

Chantilly, VA

$117K - $140K/yr

Enterprise Data Engineer Chantilly, VA TS/SCI and FSP is Required $200K to $250K We are seeking skilled and detail-oriented Data Engineers with expertise in utilizing Python, SQL, and ETL to extract ...

ASPCA

Senior Enterprise Data Engineer

$138K - $143K/yr

Overview The Senior Enterprise Data Engineer will play a critical role in designing, building, and maintaining the ASPCA's enterprise data warehouse ecosystem. This role will be part of the ...

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Enterprise Data Engineer information

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$44.5K

$129.7K

$177.5K

How much do enterprise data engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for enterprise data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is an Enterprise Data Engineer?

An Enterprise Data Engineer is a professional responsible for designing, building, and managing large-scale data infrastructure and pipelines within an organization. They ensure that data is collected, stored, processed, and made available efficiently and securely across the enterprise. Their work supports analytics, business intelligence, and decision-making by enabling reliable data flow between systems. Enterprise Data Engineers often collaborate with data scientists, analysts, and IT teams to implement best practices in data architecture, governance, and integration.

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

To thrive as an Enterprise Data Engineer, you need a solid background in data modeling, database management, and programming languages such as SQL, Python, or Scala, usually supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), ETL tools, and cloud services (such as AWS, Azure, or Google Cloud) is typically required, along with relevant certifications. Strong problem-solving abilities, collaboration, and effective communication are standout soft skills in this role. These skills and qualities are essential for building scalable data solutions, ensuring data integrity, and facilitating cross-functional business insights.

How does an Enterprise Data Engineer typically collaborate with other teams within an organization?

Enterprise Data Engineers frequently work alongside data scientists, business analysts, and IT teams to design and implement robust data pipelines and architectures. They play a crucial role in translating business requirements into scalable data solutions and often participate in cross-functional meetings to ensure alignment on data strategy and governance. Effective communication and teamwork are essential, as data engineers must coordinate with stakeholders to ensure data quality, accessibility, and security across various enterprise platforms.
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What job categories do people searching Enterprise Data Engineer jobs look for? The top searched job categories for Enterprise Data Engineer jobs are:
Enterprise Data Engineer jobs near you
Infographic showing various Enterprise Data Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Enterprise Data Engineer

GRVTY

Chantilly, VA

$117K - $140K/yr

Other

Posted 22 days ago

Job description

What Impact You'll Have

GRVTY provides tactical data engineering solutions. We embed skilled Data Engineers, Data Scientists, and ETL Developers directly into intelligence analyst groups to be their go-to data wranglers. We develop new tools, code, and services to execute data engineering activities. Our engineers work to collect, process, and feed analytic tools, turning data into intelligence in response to immediate mission needs, with direct impact on real world situations. You will see your work used here on a daily basis, and you'll have the opportunity to support a variety of Sponsor mission organizations and mission partner organizations.

What You'll be Owning

GRVTY is seeking an Enterprise Data Engineer with a TS/SCI + Poly clearance (applicable to this customer) to join one of our top projects in Chantilly, VA.  The successful Enterprise Data Engineer must be a skilled and detail-oriented professional with expertise in utilizing Python, SQL, and Palantir (or other ETL platforms) to extract, transform, and load structured and unstructured data from various sources.  They must have a strong background in data engineering and a deep understanding of ETL processes.

In this role you will:

  • Write robust and efficient Python and SQL scripts to automate data processing tasks
  • Integrate data from diverse sources, such as databases, APIs, and flat files, into centralized systems
  • Implement data transformations, enrichment, and modeling workflows to ensure data quality and usability
  • Ensure data structures are optimized for performance and scalability
  • Provide technical guidance and support to ensure effective use of Palantir tools across teams
  • Implement data quality checks, validation, and monitoring mechanisms to ensure the accuracy and reliability of datasets
  • Integrate data from diverse sources, such as databases, APIs, and flat files, into centralized systems
  • Ensure proper data transformation and curation to meet business and analytics requirements
  • Maintain and improve data quality, consistency, and accuracy through validation and cleansing processes

What You Must Have

  • Active TS/SCI with Polygraph Clearance (applicable to this customer)
  • 3+ years of experience in data engineering
  • Strong proficiency in scripting and programming with Python
  • Expertise in working with SQL for data querying, transformation, and optimization
  • Experience with data integration from diverse sources such as APIs, relational databases, and file systems
  • Strong analytical and problem-solving skills with attention to detail
  • Excellent communication and teamwork skills to collaborate with technical and business teams

What Would be Nice to Have

  • Bachelor's degree in Computer Science, Data Engineering, or a related field
  • Hands-on experience with Palantir
  • Experience with cloud platforms(e.g., AWS, Azure, GCP) and big data technologies (e.g., Apache Spark, Hadoop)
  • Familiarity with data orchestration toolssuch as Apache Airflow, Prefect, or similar

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