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# Data Engineer

- **Company:** Absolute Business Solutions Corp
- **Location:** Herndon, VA, United States
- **Experience:** Experienced
- **Salary:** $120,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Business Analytics Applications, Data Analysis, Confluence, JIRA, Microsoft Azure, Big Data, Cloud Computing, Collaborative Software, Computer Programming, Databases, Continuous Integration, Information Engineering, Data Presentation, Distributed Data Store, MapReduce, Python (Programming Language), Machine Learning, Natural Language Processing, Cloudera, Scala (Programming Language), Software Engineering, SQL Databases, Data Streaming, Workflow Management Systems, Parquet, Data Processing, Enterprise Software Applications, Large Language Models, Apache Spark, Electronic Medical Records, Git, Data Lakes, Pyspark, Apache Flink, Production Code, Apache Nifi, Machine Learning Operations, Restful APIs, GPT, Data Pipelines, Docker, Jenkins, Databricks
- **Published:** October 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fcc39b06e0d0832a

## About the Role

We're interested in candidates with hands-on experience in Databricks, Apache Spark, or Java-based data application development. The right candidate may come from a data engineering, software development, data science, or machine learning background and can work effectively with both technical teams and mission stakeholders., * Active TS/SCI security clearance with willingness to obtain and maintain counterintelligence polygraph.

 * Bachelor's degree and at least 2 years of relevant experience in data engineering, software development, data science, analytics, or machine learning; additional relevant experience may substitute for a degree.
 * Hands-on experience with at least one of the following:
 + Databricks
 + Apache Spark, including PySpark or Scala
 + Java-based data processing or enterprise application development
 * Experience working with data using SQL and at least one programming or analytical language, such as Python, Java, Scala, or R.
 * Experience building, supporting, or maintaining data pipelines, analytical solutions, or production software.
 * Understanding of data quality, validation, and troubleshooting.
 * Ability to work effectively with engineers, analysts, customers, and other stakeholders.
 * Strong written and verbal communication skills., * 5 or more years of relevant experience, particularly in data engineering or large-scale data processing.
 * Experience with Delta Lake, Parquet, Structured Streaming, or lakehouse architectures.
 * Experience with distributed data systems or big data platforms such as Flink, MapReduce, EMR, Dataproc, Cloudera, or Hortonworks.
 * Experience with containers and orchestration tools such as Docker and Kubernetes.
 * Experience with object storage, including S3-compatible systems.
 * Experience developing, deploying, or maintaining machine learning models and AI/ML data pipelines.
 * Familiarity with orchestration tools such as Airflow, dbt, or NiFi.
 * Experience with cloud platforms such as AWS, GCP, or Azure.
 * Experience with CI/CD, Git, Jenkins, REST APIs, or infrastructure as code.
 * Knowledge of statistics, probability, NLP, image processing, or A/B testing.
 * Familiarity with LLMs and GPT models.
 * Prior experience supporting NGA, DoD, or Intelligence Community programs.
 * Experience presenting data-driven findings to customer or business stakeholders.
 * Familiarity with JIRA, Confluence, or similar collaboration tools.

## Description

* Build, maintain, and optimize data pipelines and data products for large-scale data processing.
 * Develop solutions using Databricks, Apache Spark, Java, or related technologies, based on the mission and team needs.
 * Ingest, transform, validate, and prepare data for analytics, machine learning, and downstream applications.
 * Develop, deploy, and maintain analytical or machine learning models where appropriate to the work.
 * Apply statistical and data science methods to identify patterns, answer customer questions, and produce actionable insights.
 * Tune data processing and Spark workloads for performance, reliability, and efficient storage.
 * Work with distributed data systems, data lakes, and formats such as Parquet and Delta Lake.
 * Integrate data products with databases, APIs, analytics platforms, and AI/ML workflows.
 * Explain findings and recommendations to nontechnical stakeholders and collaborate with engineering teams on implementation.
 * Troubleshoot data quality, pipeline, and model issues in secure environments, including air-gapped systems when required.
 * Contribute to production-quality code, documentation, and collaborative development practices.