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Data Engineer With Jobs (NOW HIRING)

Data Engineer with DevOps

Dallas, TX ยท On-site

$52.25 - $71.50/hr

Senior Data Engineer with DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 Days Onsite Years Of Exp : 8+ Yrs We are seeking a Data Engineer with 5 ...

Data Engineer with DevOps

Dallas, TX ยท On-site

$52.25 - $71.50/hr

Senior Data Engineer with DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 Days Onsite Years Of Exp : 8+ Yrs We are seeking a Data Engineer with 5 ...

Senior Data Engineer with MDM

Iselin, NJ ยท On-site

$107K - $146K/yr

Job title- Senior Data Engineer with MDM Location- Iselin, NJ (Need Onsite day 1, hybrid 3 days from office) . Our Client is seeking a Senior Data Engineer with MDM experience to join our team in ...

Data Engineer

Denver, CO ยท On-site

$117K - $141K/yr

Onsite Denver CO (Only local Profiles) Required Skills - SQL Developer, Snowflake Nice to have skills - Python, DB scripting Job Summary โ€ข Data Engineer with 8 years of experience and good exposure ...

Data Engineer

Chantilly, VA ยท On-site

$150K - $250K/yr

This role, requires working with a team of developers, data scientists, SMEs, and cyber analysts to design, develop, build, and analyze data management systems. The Data Engineer will work with and ...

Data Engineer

Herndon, VA ยท Hybrid

$117K - $141K/yr

Experience with data transfer tools (Ex: NiFi, Cribl, etc) * Establishes data standards and acts as ... Systems Engineer with Data Engineer background * Ability to manage and troubleshoot data feeds

Data Engineers with Lumi

Phoenix, AZ ยท On-site

$113K - $136K/yr

... Data Engineer with a solid experience of building Bigdata, Google Cloud Platform Cloud based ETL Pipelines and Spark applications, strong problem-solving skills, articulate communications, and a ...

... a Data Engineer specializing in MemSQL. The role involves designing, developing, and maintaining data pipelines and architectures, collaborating with stakeholders to ensure data systems are robust ...

Data Engineer

NJ ยท On-site

$116K - $140K/yr

New Jersey / Irving, TX / Tampa, FL We are looking for an experienced Data Engineer with strong expertise in MEM SQL (SingleStore) to join our team supporting Incedo projects. The ideal candidate ...

Data Engineer

Texas City, TX ยท On-site

$98K - $117K/yr

Data Engineer We are looking for an experienced Data Engineer with 8+ years of experience in designing, developing, and maintaining scalable data solutions. Responsibilities * Design and develop data ...

Data Engineer - Only Locals

Atlanta, GA ยท On-site

$110K - $132K/yr

The ideal candidate will have strong hands-on experience with data integration, ETL/ELT, cloud technologies, SQL, and modern data engineering tools. The candidate should be able to work onsite in ...

Snowflake Data Engineer (Azure) - Full-Time | Wilmington, DE We are actively seeking an experienced Snowflake Data Engineer with Azure expertise to join our team in Wilmington, DE on a full-time ...

Showing results 21-40

Data Engineer With information

See salary details

$44.5K

$129.7K

$177.5K

How much do data engineer with jobs pay per year?

As of Sep 15, 2026, the average yearly pay for data engineer with 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 the difference between Data Engineer With vs Data Scientist?

AspectData Engineer WithData Scientist
Required CredentialsBachelor's in CS, Engineering, or related field; certifications like AWS, GCP, or AzureBachelor's or higher in CS, Statistics, or related; often with certifications in data analysis or machine learning
Work EnvironmentBuild and maintain data pipelines, databases, and infrastructureAnalyze data, develop models, and generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data infrastructure is criticalResearch institutions, tech firms, marketing, and analytics-focused companies

While Data Engineers With focus on developing and maintaining data infrastructure, Data Scientists analyze data to derive insights. Both roles often collaborate but serve different functions within data teams.

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Cities with the most Data Engineer With job openings:

What states have the most Data Engineer With jobs?

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What are popular job titles related to Data Engineer With jobs?

For Data Engineer With jobs, the most frequently searched job titles are:

Infographic showing various Data Engineer With job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer with Security Clearance

Winchester, VA โ€ข On-site

$61 - $82/hr

Other

Re-posted 15 days ago


Job description

Senior Data Engineer Location: Winchester, VA
Clearance: Active Top Secret Role Level: Senior
Work Environment: On-site / mission-focused federal environment
Pay Rate: $61-82/hr depending on experience/LCAT Overview We are seeking a Senior Data Engineer to support the design, development, and delivery of advanced visual analytics applications for a federal law enforcement mission. This role will focus on building data-driven solutions that transform structured and semi-structured information into actionable intelligence for operational users. The ideal candidate has strong hands-on experience with data engineering, data analytics, relational data analysis, visualization technologies, and large-scale data processing. This position will support the full data lifecycle, including ingestion, transformation, storage, analytics, visualization, and performance optimization. Key Responsibilities
Develop and support advanced data analytics capabilities for desktop and web-based visual analytic applications
Engineer data solutions that transform structured and semi-structured data streams into usable, actionable intelligence
Support the bulk analysis of relational information using visualization tools, advanced graphics, and high-performance computing techniques
Build, maintain, and optimize data pipelines to ingest, process, and prepare data for analytical use
Design and implement data models, database structures, and analytical workflows to support operational reporting and intelligence analysis
Integrate data from multiple sources into scalable analytics environments
Develop backend data services and processing logic to support visual analytic software platforms
Support the use of open-source, commercial, and government-developed technologies within the data environment
Design strategies for enterprise database systems, including standards for operations, programming, performance, and security
Construct and maintain large relational databases supporting mission and analytic workloads
Refine database and application performance to improve speed, reliability, and functionality
Integrate new systems and data sources with existing warehouse and analytics structures
Collaborate with software developers, analysts, engineers, and mission stakeholders to translate data needs into technical solutions
Troubleshoot data issues, pipeline failures, database performance concerns, and integration challenges
Maintain documentation for data pipelines, data models, workflows, and technical processes Required Qualifications
Bachelorโ€™s degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related technical field
Senior-level experience in data engineering, data analytics, database development, or related technical disciplines
Strong experience designing, developing, and supporting data pipelines
Experience working with structured and semi-structured datasets
Strong knowledge of relational databases and enterprise data warehouse concepts
Experience developing and optimizing SQL queries, database objects, and data transformation processes
Experience supporting visual analytics, dashboards, reporting platforms, or related analytic applications
Ability to support data integration across multiple systems and sources
Strong understanding of data modeling, data quality, and database performance optimization
Ability to work with technical and mission stakeholders to define requirements and deliver usable data solutions
Strong analytical, troubleshooting, and communication skills Preferred Qualifications
Experience supporting federal law enforcement, national security, intelligence, or defense programs
Experience with high-performance computing or large-scale data processing environments
Experience developing analytics for web-based or desktop visual analytic software
Experience with open-source, COTS, or GOTS technologies
Experience with data warehouse modernization or integration efforts
Experience supporting mission systems that produce operational or investigative intelligence
Familiarity with cloud-based data platforms, distributed processing, or scalable analytics architectures
Experience with data visualization tools or advanced graphical analytics capabilities Desired Technical Skills
SQL
Python
ETL / ELT
Data Pipelines
Data Warehousing
Relational Databases
Data Modeling
Data Transformation
Data Visualization
Structured and Semi-Structured Data
High-Performance Computing
Web-Based Analytics Applications
Desktop Analytics Applications
Open-Source / COTS / GOTS Technologies
Performance Tuning
Database Security
Data Integration What Makes a Strong Candidate
Strong data engineering foundation with the ability to move from raw data to actionable intelligence
Comfortable supporting large, complex data environments with multiple source systems
Able to balance backend data engineering with user-facing analytics needs
Strong problem solver who can troubleshoot pipelines, databases, and integration issues
Mission-focused mindset with the ability to support sensitive federal operations
Clear communicator who can work across engineering, mission, and analyst teams
Detail-oriented approach to data quality, system performance, and operational reliability