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Data Services Engineer Jobs (NOW HIRING)

Data Engineer

Reston, VA

$119.10K - $143K/yr

Position Summary ANSER is seeking a Data Engineer to design, build, and optimize enterprise-level ... Monitor, maintain, and upgrade data services, content management systems, and databases; analyze ...

Develop and promote data services and programming related to the full research data cycle across the library and campus. * Contribute to the team's portfolio of services by providing consultations ...

Description VAST Data is looking for a Professional Services Engineer to join our growing team! This is a great opportunity to be part of one of the fastest-growing infrastructure companies in ...

Description VAST Data is looking for a Professional Services Engineer to join our growing team! This is a great opportunity to be part of one of the fastest-growing infrastructure companies in ...

Data Engineer

Reston, VA · On-site

$119.10K - $143K/yr

Because we were established for the purpose of public service and not for profit, we measure our success in the impact of our service. Position Summary ANSER is seeking a Data Engineer to design ...

Data Engineer

Bellevue, WA · On-site

$129.20K - $155.20K/yr

Data Engineer Job Location: Bellevue - Washington Job Type: Contract to Hire * Design build and ... Lead the integration of cloudnative data services eg Azure Synapse ADLS Azure SQL Cosmos DB into ...

With unstructured data growing in more locations faster than ever before, enterprises today need a ... About The Position Engineers working on core services build the modern distributed storage engine ...

... engineering, and client services teams to deliver robust, scalable, and secure data pipelines and ... platforms. Responsibilities: Leadership & Strategy * Define and execute the data services roadmap ...

Define, develop and maintain secure, reliable, and scalable Infra services that meet Wolfspeed ... Data Cetner Operations team, its Partner engineers to provide key input to technical design ...

With unstructured data growing in more locations faster than ever before, enterprises today need a ... About The Position Engineers working on core services build the modern distributed storage engine ...

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Data Services Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do data services engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for data services 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 are the key skills and qualifications needed to thrive as a Data Services Engineer, and why are they important?

To thrive as a Data Services Engineer, you need expertise in database management, data integration, and strong programming skills, typically supported by a degree in computer science or a related field. Familiarity with SQL, ETL tools, cloud platforms (like AWS or Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong problem-solving skills, attention to detail, and effective communication distinguish top performers in this role. These capabilities ensure efficient data operations, robust system performance, and seamless collaboration across technical and business teams.

What are some typical challenges Data Services Engineers encounter when managing large-scale data pipelines?

Data Services Engineers often face challenges related to maintaining data integrity and optimizing pipeline performance as data volumes grow. Ensuring that data flows smoothly between different systems, handling schema changes, and minimizing downtime during updates are common hurdles. Collaboration with data analysts, data scientists, and DevOps teams is crucial to troubleshoot issues and implement best practices. Staying up to date with evolving technologies and automating routine tasks can help address these challenges efficiently.

What are Data Services Engineers?

Data Services Engineers are professionals who design, build, and maintain systems that manage, process, and deliver data across an organization. They work with databases, data pipelines, and cloud platforms to ensure reliable data access for analytics and business operations. Their responsibilities often include data integration, data quality assurance, and supporting data-driven applications. Data Services Engineers collaborate closely with data scientists, analysts, and software engineers to support the organization's data infrastructure needs.

What is the difference between Data Services Engineer vs Data Engineer?

AspectData Services EngineerData Engineer
CredentialsBachelor's in CS, Data Science, or related; certifications like AWS, Azure, or Google CloudBachelor's in CS, Software Engineering, or related; similar cloud certifications
Work EnvironmentFocus on data integration, ETL processes, and data pipeline managementDesign, build, and maintain data architecture and pipelines
Employer & Industry UsageUsed in data-driven companies, analytics teams, cloud service providersCommon in tech firms, finance, healthcare, and any organization with large data needs

While both roles involve working with data pipelines and cloud platforms, Data Services Engineers primarily focus on data integration, ETL processes, and ensuring data accessibility. Data Engineers tend to design and develop the overall data architecture and infrastructure. The roles often overlap, but the Data Services Engineer is more specialized in data delivery and integration tasks.

More about Data Services Engineer jobs
What cities are hiring for Data Services Engineer jobs? Cities with the most Data Services Engineer job openings:
Infographic showing various Data Services Engineer job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 94% Physical, 3% Hybrid, and 3% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

$119.10K - $143K/yr

Other

Posted 19 hours ago


Job description

Position Summary

ANSER is seeking a Data Engineer to design, build, and optimize enterprise-level data management systems to support Object-Based Intelligence (OBI) analytic processes and mission requirements. You will focus on integrating and maintaining scalable, secure data pipelines and architectures that enable advanced analytic workflows, visualization, and automation.

Day-to-Day Responsibilities

  • Manage complex, long-term projects involving the design, development, integration, and installation of new information systems, databases, and data services.
  • Perform technical studies, systems analysis, and feasibility assessments to ensure designs meet user requirements and define specifications for new or existing data and content management solutions.
  • Design, develop, integrate, install, and optimize data management capabilities, data integration solutions, and both relational and non-relational databases (e.g., PostgreSQL) to support enterprise ingestion, storage, retrieval, and analytics.
  • Collaborate with team members to design, refine, implement, and maintain resilient, scalable ETL pipelines using industry-standard tools and frameworks (e.g., Apache NiFi).
  • Ensure ETL pipelines support secure data acquisition, normalization, enrichment, and delivery while meeting security controls, SLA requirements, and evolving data architecture needs.
  • Collaborate with team members to design, implement, and maintain GraphQL APIs enabling flexible, efficient access and aggregation of data across distributed enterprise sources.
  • Conduct testing and promote the integration of new databases and data services within existing IT infrastructure, including operational readiness testing and transitional user support.
  • Create, execute, and document comprehensive test plans covering component, integration, system, compatibility/interface, user acceptance, and performance/stress testing.
  • Monitor, maintain, and upgrade data services, content management systems, and databases; analyze system and database reports to ensure optimal performance.
  • Identify data redundancy and design solutions to integrate or consolidate sources, reducing storage and maintenance costs while improving enterprise consistency.
  • Produce technical data, performance reporting, and analysis outlining the operational characteristics of databases and data services across the DIA/DIE infrastructure.
  • Develop and maintain disaster recovery and continuity plans to ensure data availability, access reliability, and database integrity during crisis situations.
  • Analyze, evaluate, and provide recommendations, artifacts, and integration patterns for current, planned, and emerging data service, data management, and database technologies based on performance, cost, and security requirements.
  • Design, develop, test, and implement unstructured data management solutions, including content extraction, tagging, data integration, web services, service versioning, containerization (e.g., Docker, Kubernetes), and infrastructure-as-code automation.
  • Troubleshoot service, database, and user interface failures; implement temporary fixes and permanent corrections; interface with vendors, developers, and users; manage change requests; support code repositories; and prepare and present technical briefings to senior leadership.

Required Qualifications

  • TS/SCI with Poly Clearance
  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical discipline.
  • Eight (8) or more years of experience in data engineering.
  • Proven experience developing and managing data pipelines, ETL processes, and database systems for large-scale or mission-critical environments.
  • Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
  • Experience with data orchestration and automation tools (e.g., Apache NiFi, Airflow, or similar).
  • Familiarity with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
  • Experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.
  • Strong understanding of data security, access control, and system hardening in accordance with DoD and IC standards.
  • Demonstrated ability to apply semantic data modeling and metadata standards within an OBI or analytic environment.
  • Proficiency in containerization and orchestration technologies such as Docker and Kubernetes.

Preferred Qualifications

  • Master's degree in Data Science, Computer Engineering, or related field.
  • Familiarity with semantic web technologies (RDF, OWL, SPARQL) and their use in OBI data integration.
  • Understanding of advanced analytic method augmentation.
  • Experience developing data visualization and analytic tools supporting structured and unstructured intelligence data.
  • Certification in Data Management or Cloud Architecture (e.g., AWS Certified Data Engineer, Google Professional Data Engineer).
  • Ability to communicate technical data management concepts clearly to both technical and non-technical audiences.
  • Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
  • Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
  • Experience working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).
  • Experience developing OBI governance and tradecraft to assist DIA and other DIAAE organizations conducting OBI.