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Elt Developer Jobs in Virginia (NOW HIRING)

Anika Systems

Data Engineer

Leesburg, VA · On-site +1

$115K - $139K/yr

The ideal candidate has hands-on experience with ETL/ELT pipelines, XBRL data processing, Apache ... Ability to work in Agile, DevOps-oriented environments. * U.S. Citizenship required; ability to ...

IT America Inc

Data Engineer

Mclean, VA · On-site

$115K - $139K/yr

Work in Agile teams, following CI/CD and DevOps best practices. Required Skills & Experience: * Strong experience in Data Engineering with hands-on development of ETL/ELT workflows. * Expertise in ...

Harmonia Holdings Group, LLC.

Data Engineer

Mclean, VA · Remote

$117K - $141K/yr

... developer responsible for building, maintaining, and optimizing data pipelines and data services ... Design, develop, and maintain ETL/ELT pipelines for secure data ingestion, transformation, and ...

Revolutional, LLC

Data Engineer

Mclean, VA · Remote

$115K - $139K/yr

... developer responsible for building, maintaining, and optimizing data pipelines and data services ... Design, develop, and maintain ETL/ELT pipelines for secure data ingestion, transformation, and ...

Acuity INC

Senior Data Engineer

Reston, VA

$110K - $150K/yr

This role builds and maintains robust data integration, ETL/ELT, and analytic processing ... Databricks Certified Developer for Apache Spark * Databricks Certified Data Engineer Associate

Acuity INC

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

This role builds and optimizes ETL/ELT workflows across the data warehouse, data lake, and ... The Data Engineer delivers reliable, secure, and high-performing data solutions that support ...

Acuity INC

Data Engineer

Reston, VA

$119K - $143K/yr

This role builds and optimizes ETL/ELT workflows across the data warehouse, data lake, and ... The Data Engineer delivers reliable, secure, and high-performing data solutions that support ...

Acuity INC

Senior Data Engineer

Reston, VA · On-site

$110K - $150K/yr

This role builds and maintains robust data integration, ETL/ELT, and analytic processing ... Databricks Certified Developer for Apache Spark * Databricks Certified Data Engineer Associate

IntelliTech LLC

Mid Data Engineer

Arlington, VA · On-site

Develop robust ETL/ELT solutions across structured and unstructured data sources, including APIs ... Collaborate with engineers, analysts, data scientists, and other stakeholders to support reporting ...

IntelliTech

Mid Data Engineer

Arlington, VA · On-site

$110K - $180K/yr

Develop robust ETL/ELT solutions across structured and unstructured data sources, including APIs ... Collaborate with engineers, analysts, data scientists, and other stakeholders to support reporting ...

Pyramid Systems

Sr. Data Engineer

Fairfax, VA · On-site

$113K - $136K/yr

Sr. Data Engineer Job ID 2026-2176 # of Openings 1 Overview Pyramid Systems is looking for a Data ... Experience with ETL and ELT tools such as SSIS, Pentaho, and/or Data Migration Services * Advanced ...

SCCI

Database Developer

Dahlgren, VA · On-site

Experience with ETL/ELT pipelines and large-scale data transformation * Strong understanding of ... Programming experience (Python, Java, or similar) for data processing and automation SCCI is ...

Beyond SOF

Agentic Engineer.

Richmond, VA

$106K - $127K/yr

Develop and manage Extract, Load, Transform (ELT) processes to ensure data is accurately and ... Collaborate with data scientists and engineers to preprocess data, train models, and integrate AI ...

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Elt Developer information

What are the key skills and qualifications needed to thrive as an ELT Developer, and why are they important?

To thrive as an ELT Developer, you need strong proficiency in database management, data warehousing concepts, and programming languages such as SQL and Python, often supported by a degree in computer science or a related field. Familiarity with ETL/ELT tools like Informatica, Talend, Apache NiFi, or cloud-based platforms such as AWS Glue and Azure Data Factory is typically required. Analytical thinking, problem-solving skills, and effective communication help you understand complex data requirements and collaborate with cross-functional teams. These skills and qualities are critical to ensure efficient, accurate data integration and transformation processes that support business intelligence and decision-making.

What are ELT Developers?

ELT Developers are professionals who specialize in designing, building, and maintaining data pipelines using the Extract, Load, Transform (ELT) process. They extract data from various sources, load it into a data warehouse or data lake, and then transform it within the storage system to support analytics and business intelligence. ELT Developers work with tools and platforms such as SQL, cloud data warehouses (like Snowflake or BigQuery), and ETL/ELT frameworks to ensure data is accurate, accessible, and well-structured for analysis.

How do ELT Developers typically collaborate with data analysts and engineers on projects?

ELT Developers often work closely with data analysts to understand data requirements and ensure the transformed data meets analytical needs. They also partner with data engineers to design and optimize pipelines for efficient data extraction, loading, and transformation. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth collaboration. Clear communication and teamwork are essential, as ELT Developers serve as a bridge between raw data sources and actionable business insights.

What is the difference between Elt Developer vs Data Engineer?

AspectElt DeveloperData Engineer
Required CredentialsBachelor's in CS or related field, knowledge of XML, XSLT, scriptingBachelor's in CS, experience with databases, programming, ETL tools
Work EnvironmentContent management, language localization, data transformation projectsData pipeline development, large-scale data processing, infrastructure setup
Employer & Industry UsageTech companies, localization firms, e-learning providersFinance, healthcare, tech firms managing big data

While both roles involve working with data, Elt Developers focus on language data transformation and localization tasks, whereas Data Engineers build and maintain data pipelines for large-scale data processing. The roles share some technical skills but differ in scope and industry focus.

Elt Developer jobs near you
Data Engineer

Data Engineer

Anika Systems

Leesburg, VA • On-site, Remote

$115K - $139K/yr

Full-time

Posted 17 days ago

Job description

Anika Systems is seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines and platforms supporting federal clients. This role will play a critical part in enabling enterprise data strategies, supporting Office of the Chief Data Officer (OCDO) initiatives, and delivering high-quality, trusted data for analytics, reporting, and mission operations.
This opportunity is 100% remote.
The ideal candidate has hands-on experience with ETL/ELT pipelines, XBRL data processing, Apache Iceberg-based architectures, and advanced data optimization techniques such as materialized views and context-aware data engineering. This role also requires proficiency in AI tools and AI-assisted development workflows, along with experience building and deploying CI/CD pipelines for data and analytics platforms.
Key Responsibilities
Data Pipeline Development & ETL/ELT
  • Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data across enterprise platforms.
  • Build scalable data ingestion frameworks for structured and semi-structured data, including XBRL filings and financial datasets.
  • Implement data transformation logic to support analytics, reporting, and regulatory use cases.
  • Ensure data pipelines are reliable, performant, and scalable in cloud environments.
  • Leverage AI-assisted development tools to accelerate pipeline development, testing, and optimization.
Cloud Data Platforms & Iceberg Architecture
  • Develop and manage data solutions leveraging AWS services (e.g., S3, Airflow, DAGs, Glue, Lambda, Redshift).
  • Implement and optimize Apache Iceberg table formats for large-scale, ACID-compliant data lakes.
  • Support lakehouse architectures that unify data lakes and data warehouses.
  • Optimize data storage and retrieval strategies for performance and cost efficiency.
  • Enable data platforms that support AI/ML workloads and downstream generative AI use cases.
CI/CD & DataOps Engineering
  • Design and implement CI/CD pipelines for data pipelines, infrastructure, and analytics code using tools such as GitHub Actions, GitLab CI, Jenkins, or AWS-native services.
  • Automate build, test, and deployment processes for ETL pipelines and data platform components.
  • Implement DataOps best practices, including version control, automated testing, environment promotion, and rollback strategies.
  • Ensure reproducibility, reliability, and governance of data pipeline deployments across environments.
  • Integrate AI-driven testing and monitoring tools to improve pipeline quality and reduce operational risk.
Data Optimization & Performance Engineering
  • Design and implement materialized views and other performance optimization techniques to improve query efficiency.
  • Tune data pipelines and queries for performance, scalability, and cost.
  • Implement partitioning, indexing, and caching strategies aligned to workload patterns.
XBRL & Financial Data Processing
  • Develop pipelines to ingest, parse, and normalize XBRL (eXtensible Business Reporting Language) data.
  • Support regulatory and financial data use cases requiring high accuracy and traceability.
  • Ensure alignment with data standards and validation rules for financial reporting datasets.
Context Engineering & Data Modeling Support
  • Apply context engineering principles to ensure data is enriched with meaningful metadata, lineage, and business context.
  • Collaborate with Data Architects to support data modeling, schema design, and entity relationships.
  • Enable downstream analytics and AI use cases by structuring data for usability, discoverability, and governance.
Metadata, Data Catalog, and Governance Integration
  • Integrate pipelines with enterprise data catalogs and metadata management systems.
  • Support automated metadata capture, lineage tracking, and data quality monitoring.
  • Ensure alignment with data governance frameworks and standards established by OCDO organizations, including AI data readiness and traceability.
Stakeholder Collaboration & Agile Delivery
  • Collaborate with data architects, analysts, and business stakeholders to understand data needs and deliver solutions.
  • Participate in stakeholder listening campaigns, workshops, and data discovery efforts.
  • Work in Agile teams to iteratively deliver data capabilities and enhancements.
  • Contribute to identifying and implementing AI-driven efficiencies and automation opportunities across the data lifecycle.
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
  • 5+ years of experience in data engineering, ETL development, or data platform engineering.
  • Strong hands-on experience with:
    • ETL/ELT tools and frameworks
    • AWS data services (S3, Glue, Lambda, Redshift, etc.)
    • Apache Iceberg and modern data lake architectures
  • Experience designing and implementing CI/CD pipelines for data platforms and ETL workflows.
  • Demonstrated proficiency using AI tools and AI-assisted development workflows (e.g., LLM copilots, automated code generation, pipeline optimization tools).
  • Experience processing XBRL or complex financial/regulatory datasets.
  • Proficiency in SQL and Python.
  • Experience implementing materialized views and query optimization techniques.
  • Understanding of data modeling concepts and metadata management.
  • Familiarity with data governance, data quality practices, and data readiness for AI/ML use cases.
  • Ability to work in Agile, DevOps-oriented environments.
  • U.S. Citizenship required; ability to obtain and maintain a federal clearance.
Preferred Qualifications
  • Experience supporting federal agencies such as SEC, DHS, Treasury, or Federal Reserve System.
  • Familiarity with data catalog tools (e.g., Collibra, Alation, ServiceNow).
  • Experience with Apache Spark, Kafka, or other distributed data processing frameworks.
  • Experience enabling data pipelines for AI/ML or generative AI applications.
  • Knowledge of data maturity frameworks (e.g., EDM DCAM, TDWI).
  • Exposure to context engineering or semantic data layer design.
  • AWS or data engineering certifications.
  • Experience with infrastructure-as-code (IaC) tools (e.g., Terraform, CloudFormation) in support of CI/CD pipelines.

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