Data Engineer with Security Clearance

Responsibilities

• Movement of structure and unstructured data using approved methods.
• Execute data ingestion activities for storing data in a local or enterprise level location.
• Develop code to format data that supports exploration.
• Analyze source data formats and work with Data Scientists and partners to determine the formats and transforms that best meet mission objectives.
• Develop code and tools to provide one-time and on-going data extraction from various repositories, formatting and transformations into enterprise or standalone data models.
• Develop and deliver documentation for each project including ETL mappings, code use guide, code location and access instructions.
• Design and optimize Data Pipelines using tools such as Spark, Apache Iceberg, Trino, OpenSearch, EMR cloud services, NiFi and Kubernetes containers.
• Ensure the pedigree and provenance of the data is maintained such that the access to data is protected.
• Clean and preprocess data to enable access for advanced analytics.
• Collaborate with enterprise working groups to advance the state of data standards.
• Collaborate with the engineering team, data stewards, and mission partners to aid in getting actionable value out of the data holdings.
• Collaborate with software engineers to update, configure, and maintain data services based on the requirements.
• Ensure data quality by working with the testing and data quality team to enhance standardization of data conditioning pipelines.

Requirements

• 10+ years experience with:
• Data lifecycle engineering
• Development and maintenance of extract, transform and load (ETL) tools and services
• Cloud and on-prem data storage and processing solutions
• Python, SQL, Spark and other data engineering programming
• COTS and open source data engineering tools such as ElasticSearch and NiFi
• Processing data within the Agile Lifecycle