Data Engineer

Volume Integration•Chantilly, VA

36d

About The Position

Are you passionate about building scalable data pipelines and working with complex datasets in cloud environments? NS2 Mission is seeking a skilled Data Engineer to support mission-focused programs in Chantilly, VA. In this role, you will design and maintain data pipelines, collaborate closely with development teams, and help deliver reliable data solutions that enable teams to transform data into actionable insights.

Requirements

4+ years of experience building and managing data pipelines
4+ years working within highly collaborative development teams
2+ years of hands-on experience with Python
Experience working in AWS cloud environments
Experience processing data using Spark
Experience working with relational databases such as PostgreSQL, Oracle, or MySQL, including writing SQL queries
Experience working in Linux environments, including shell scripting
Experience analyzing data across multiple formats such as CSV, XML, JSON, Avro, and Parquet
Experience writing and maintaining unit tests

Nice To Haves

Experience using Apache NiFi, Apache Airflow, or similar orchestration tools to manage data pipelines
Development experience with Java or Scala
Experience administering or supporting EMR or Spark clusters
Background in performance tuning Spark jobs
Experience working with Hive, Iceberg, or other technologies that provide SQL-based access to large datasets
Familiarity with implementing cloud-based security solutions
Experience following configuration management processes for code review and release deployments

Responsibilities

Design, build, and maintain scalable data pipelines that support the ingestion, transformation, and delivery of large datasets
Collaborate with cross-functional development teams to integrate data solutions into applications and mission systems
Process and transform data using technologies such as Spark within cloud-based environments
Develop and optimize SQL queries to support data retrieval, transformation, and analysis
Work with relational databases including PostgreSQL, Oracle, and MySQL to manage and access structured data
Create automation and processing scripts using Python, Linux, and shell scripting
Analyze and work with datasets across multiple formats including CSV, XML, JSON, Avro, and Parquet
Write and maintain unit tests to validate data processing logic and ensure code quality
Monitor, troubleshoot, and improve the performance and reliability of data pipelines and workflows

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