Data Engineer

SAIC•Reston, VA

6h•Onsite

About The Position

SAIC is seeking a Data Engineer to support the Department of the Air Force Integrated Fires Command and Control (DIFC2) program of record. As the Data Engineer, you will design, develop, and implement data pipelines and analytics for applications. This position will collaborate with cross-functional teams to understand and address operational challenges using data pipelines and analytics. SAIC is a premier Fortune 500 mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Their robust portfolio of offerings across the defense, space, civilian and intelligence markets includes secure high-end solutions in mission IT, enterprise IT, engineering services and professional services. They integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

Requirements

Ability to design, develop, and implement data pipelines and analytics for applications.
Experience collaborating with cross-functional teams to understand and address operational challenges using data pipelines and analytics.
Proficiency in exploratory data analysis, algorithm development, and testing.
Expertise in Data Ingest, Normalization, Sanitization, Extraction, Transformation, Loading (ETL) processes for structured and unstructured data.
Familiarity with various data formats including UCI 2.0+, CSV, JSON, XML, Parquet, and ORC.
Capability to develop and deploy data pipelines and analytics in real-world operational environments.
Skills in deploying, monitoring, and optimizing data pipelines to ensure high performance and reliability.
Experience implementing event streaming pipelines using technologies like Apache Nifi Workflows, Apache Kafka, AWS Kinesis, RabbitMQ, or ZeroMQ.
Proficiency utilizing distributed computing platforms such as AWS Lambda, Dask, or Spark.
Experience leveraging cloud-native tools including AWS S3, RDS, EFS, SNS, and SQS.
Familiarity with data pipeline frameworks such as AirByte, Apache Airflow, dbt, Apache Iceberg, and Snowflake.
Ability to work with GIS data using ArcGIS, PostGIS, and related tooling.
Experience implementing containerized environments using Docker or Kubernetes.
Knowledge and application of cybersecurity principles in the context of secure DoD data applications.
Strong communication skills to effectively convey findings and engineering solutions with technical and mission stakeholders.

Responsibilities

Collaborate with cross-functional teams to understand and address operational challenges using data pipelines and analytics.
Design, develop, and implement data pipelines and analytics for applications.
Perform exploratory data analysis, algorithm development, and testing.
Perform Data Ingest, Normalization, Sanitization, Extraction, Transformation, Loading, (ETL) process of structured and unstructure data to common standards for interoperability.
Work with multiple data formats, including UCI 2.0+, CSV, JSON, XML, Parquet, and ORC.
Develop and deploy data pipelines and analytics in real-world operational environments.
Deploy, monitor, and optimize data pipelines to ensure high performance and reliability.
Implement event streaming pipelines using Apache Nifi Workflows, Apache Kafka, AWS Kinesis, RabbitMQ, or ZeroMQ.
Utilize distributed computing platforms such as AWS Lambda, Dask, or Spark.
Leverage cloud-native tools including AWS S3, RDS, EFS, SNS, and SQS.
Utilize data pipeline frameworks such as AirByte, Apache Airflow, dbt, Apache Iceberg, and Snowflake.
Work with GIS data using ArcGIS, PostGIS, and related tooling.
Implement containerized environments using Docker or Kubernetes.
Apply cybersecurity principles in the context of secure DoD data applications.
Communicate findings and engineering solutions effectively with technical and mission stakeholders.