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Data Engineer Intermediate Jobs in Washington (NOW HIRING)

This position will work closely with software developers, data engineers, cloud architects ... Intermediate" labor category as defined in the CHESS ITES-3S contract vehicle and possess the ...

This position will work closely with software developers, data engineers, cloud architects ... Intermediate" labor category as defined in the CHESS ITES-3S contract vehicle and possess the ...

This position will work closely with software developers, data engineers, cloud architects ... Intermediate" labor category as defined in the CHESS ITES-3S contract vehicle and possess the ...

This position will work closely with software developers, data engineers, cloud architects ... Intermediate" labor category as defined in the CHESS ITES-3S contract vehicle and possess the ...

Data Scientist

Chantilly, VA · On-site

$165K - $210K/yr

Data Scientist, Level 2 (Intermediate) Functional Description: In addition to being responsible for ... May conduct and/or support data engineering and data management. May assist with the selection of ...

Data Scientist

Chantilly, VA · On-site

$165K - $210K/yr

Data Scientist, Level 2 (Intermediate) Functional Description: In addition to being responsible for ... May conduct and/or support data engineering and data management. May assist with the selection of ...

Showing results 21-40

Data Engineer Intermediate information

What are some common challenges data engineer intermediates face when working with large-scale data pipelines?

As a Data Engineer Intermediate, you may frequently encounter challenges related to maintaining data quality and consistency across multiple sources, optimizing ETL processes for performance, and ensuring data pipelines are scalable to handle increasing data volumes. Troubleshooting data latency issues and managing dependencies between data sets are also common hurdles. Collaborating closely with data analysts, data scientists, and other engineers is essential to address these challenges and deliver reliable, high-quality data solutions.

What is a data engineer intermediate?

A Data Engineer Intermediate is a professional who designs, builds, and maintains data pipelines and architectures, typically with a few years of experience in the field. They are responsible for collecting, transforming, and storing data in ways that make it accessible and usable for analytics and business intelligence. Intermediate data engineers often work with tools like SQL, Python, ETL frameworks, and cloud platforms. They collaborate with data scientists, analysts, and other engineers to ensure data quality and optimize data workflows. This role requires a good understanding of data modeling, database systems, and data integration techniques.

What is the difference between Data Engineer Intermediate vs Data Engineer Junior?

AspectData Engineer IntermediateData Engineer Junior
Required CredentialsBachelor's in CS, experience with SQL, Python, ETL toolsEntry-level, basic knowledge of SQL and scripting
Work EnvironmentCollaborates on complex data pipelines, supports data architectureAssists in data tasks, learns from senior engineers
Employer & Industry UsageUsed in tech, finance, healthcare sectors for data projectsCommon in similar industries as entry-level role
Comparison Search IntentUnderstanding role progression, skills requiredEntry-level position, learning expectations

The main difference between Data Engineer Intermediate and Data Engineer Junior lies in experience, skill level, and responsibilities. Intermediate engineers handle more complex data pipelines and support data architecture, while junior engineers focus on learning foundational skills and assisting senior staff. This distinction helps employers and candidates understand career progression and required competencies.

What are the key skills and qualifications needed to thrive as a data engineer intermediate?

To thrive as a Data Engineer Intermediate, you need strong programming skills in languages like Python or Java, experience with database systems (SQL/NoSQL), and a solid understanding of data modeling, ETL processes, and data warehousing concepts. Familiarity with tools such as Apache Spark, Hadoop, Airflow, and cloud platforms like AWS or Azure, as well as relevant certifications, is highly valued. Excellent problem-solving abilities, attention to detail, and clear communication skills help set candidates apart in this role. These competencies ensure efficient data pipeline development, reliable data infrastructure, and effective collaboration with data teams and stakeholders.
What are the most commonly searched types of Data Engineer jobs in Washington? The most popular types of Data Engineer jobs in Washington are:
What cities in Washington are hiring for Data Engineer Intermediate jobs? Cities in Washington with the most Data Engineer Intermediate job openings:
Infographic showing various Data Engineer Intermediate job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Engineer with Security Clearance

Staffed4U LLC

Chantilly, VA • On-site

$118K - $142K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 18 days ago


Job description

Data Engineer Location: Chantilly, VA Work Schedule: Full-Time, Onsite Clearance Required: Active TS/SCI with Full Scope Polygraph (FSP) Employment Type: W-2 Position Overview We are seeking a talented and mission-focused Data Engineer to join our growing team supporting cutting-edge intelligence community initiatives in Chantilly, VA. This role offers the opportunity to work with large-scale datasets and contribute to the development of a custom enterprise platform supporting critical mission objectives. The selected candidate will play a key role in designing, building, and optimizing scalable data pipelines and architectures that support analytics, machine learning, and enterprise data integration efforts. This position is funded for an initial 9-12 month period aligned with defined mission deliverables and system development timelines, with all development performed onsite at the customer location. Key Responsibilities Data Engineering & Pipeline Development * Design, develop, and maintain ETL/ELT pipelines for both batch and real-time data processing using Python and SQL. * Integrate data from a variety of structured and unstructured sources, including databases, APIs, streaming platforms, PDFs, and Microsoft Office files. * Build scalable and maintainable data architectures to support analytics and machine learning workloads. * Optimize data processing workflows and queries for performance, scalability, and cost efficiency within AWS environments. * Support future pipeline scalability through exposure to PySpark and other distributed data processing frameworks. * Develop and maintain web scraping and data ingestion workflows to collect and process open-source data. * Transform collected information into structured datasets and visualizations for stakeholder analysis and decision-making. Data Management & Optimization * Collect, clean, validate, and manage large volumes of structured and unstructured data. * Implement data quality controls, validation procedures, and version management practices. * Design and optimize data storage solutions utilizing AWS S3 for raw, intermediate, and production datasets. * Implement data governance best practices including documentation, cataloging, lineage tracking, and security controls. * Ensure compliance with customer and security requirements for data management and handling. Collaboration & Machine Learning Support * Partner closely with Data Scientists, Analysts, and Engineering teams to understand business and mission requirements. * Prepare clean, structured, and feature-ready datasets for analytics and machine learning applications. * Support feature engineering, aggregation, and large-scale data transformations. * Assist with deploying machine learning models into production environments while supporting monitoring, versioning, and performance optimization. * Integrate and consume REST APIs to support data acquisition and application workflows. * Utilize Docker, Kubernetes, Git, and CI/CD pipelines to support deployment and operational workflows. Documentation & Communication * Document data pipelines, architectures, schemas, and transformation processes. * Communicate technical concepts effectively to both technical and non-technical stakeholders. * Participate in code reviews and promote engineering best practices across the team. * Contribute to continuous improvement efforts related to data engineering, automation, and platform development. Required Qualifications Experience * 3-5+ years of professional experience in Data Engineering or a related technical field. * Experience designing and implementing ETL/ELT pipelines. * Experience processing and managing large-scale structured and unstructured datasets. * Experience working in cloud-based data environments. Technical Skills * Strong proficiency with Python and SQL. * Experience with PySpark or other distributed processing frameworks (highly desired). * Experience with ElasticSearch/OpenSearch technologies. * Experience working within AWS cloud environments. * Experience supporting Linux-based systems. * Proficiency with Git for version control and collaborative development. * Understanding of machine learning workflows and MLOps concepts. * Experience integrating and consuming REST APIs. * Familiarity with Docker, Kubernetes, and CI/CD pipelines. Clearance Requirements * Active TS/SCI with Full Scope Polygraph (FSP) is required. * U.S. Citizenship required. Professional Skills * Strong collaboration and communication skills. * Ability to communicate complex technical concepts to non-technical audiences. * Detail-oriented with a strong commitment to data quality and integrity. * Ability to manage multiple priorities in a fast-paced mission environment. * Strong analytical and problem-solving capabilities. Desired Qualifications * Hands-on experience with graph databases. * Experience modeling, querying, and optimizing Neo4j databases. * Experience supporting advanced analytics, knowledge graphs, or entity resolution systems. * Experience working within Intelligence Community environments. Why Join Us? This is an opportunity to work alongside highly skilled engineers, analysts, and data scientists supporting critical national security missions. You'll have the chance to build scalable data solutions, support advanced analytics initiatives, and help shape the future of enterprise data systems in a dynamic and impactful environment. Benefits * Competitive Compensation * Comprehensive Medical, Dental, and Vision Coverage * 401(k) with Company Contribution * Paid Time Off and Company Holidays * Life and Disability Insurance * Professional Development Opportunities * Challenging and Meaningful Mission-Focused Work * Long-Term Career Growth Opportunities Equal Opportunity Employer We are committed to fostering an inclusive workplace and welcome qualified applicants from all backgrounds. Employment decisions are made without regard to race, color, religion, sex, national origin, disability, veteran status, or any other protected characteristic.