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# Spark Data Engineer (Software Engineer)

- **Company:** Ardent Principles
- **Location:** Tysons, VA, United States
- **Experience:** Experienced
- **Salary:** $130,000.0 - $260,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Data Analysis, Unit Testing, Big Data, Cloud Computing, Relational Databases, Database Queries, Linux, File Systems, JSON, Python (Programming Language), PostgreSQL, MySQL, Oracle (Applications), Performance Tuning, Shell Script, Simple Data Format, Software Deployment, Extensible Markup Language (XML), Parquet, Data Processing, Apache Spark, Avro, Apache Nifi, Data Pipelines
- **Published:** September 24, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9189775/spark-data-engineer-software-engineer

## About the Role

We are seeking a skilled Spark Data Engineer who must have hands-on experience designing, building, and maintaining scalable data pipelines while processing large datasets using Apache Spark. This role requires strong Python programming skills, expertise in cloud computing with AWS services, and experience working with relational databases such as PostgreSQL, Oracle, and MySQL.

## Description

In this challenging yet rewarding role, you are an integral part of what brings our Company's mission to life. You must have the following required skills, certifications and demonstrated experience in and/or with:
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Building and managing data pipelines
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Using Python
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Cloud computing using AWS services
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Processing data using Apache Spark
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Working with RDBMS (Postgres, Oracle, MySQL) and writing SQL queries
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Linux and shell scripting
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Analyzing data in different file formats like csv, xml, json, avro, parquet, etc.
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Writing and validating unit tests.

Highly Desired Qualifications

Other skills and demonstrated experiences that are highly desired but not mandatory to perform the work, include working with:
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Working with NiFi, Apache AirFlow, or an equivalent solution or tool for orchestrating data pipelines
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Java or Scala
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Administering an EMR/Spark cluster
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Conducting performance tuning of a spark job
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Developing cloud-based security solutions
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