Data Engineer

MANTECH

7d•$148,200 - $263,000•Remote

About The Position

MANTECH International Corporation is seeking a motivated Data Engineer for a future opportunity. The Data Engineer will be responsible for leveraging their deep understanding of performance optimization and data pipelining to enhance the usefulness of raw data for the enterprise. This role requires extensive knowledge of data manipulation tools, frameworks, and languages to construct pipelines for distributing datasets to meet the needs of downstream users.

Requirements

Bachelor’s degree in a STEM field with preference towards Computer Science and Software Engineering.
Verifiable work experience working with data structures, database management, distributed computing, and API driven architectures.
Experience with Agile Development and Git Operations.
Experience creating, maintaining, and communicating complex technical documentation for data systems.
An active Secret clearance is required with the ability to obtain and maintain TS/SCI.

Nice To Haves

Certified Data Management Professional (CDMP) certification.
Proficiency in modeling frameworks like Universal Modeling Language (UML).
Experience with the Sponsor’s primary cyber risk and compliance automation tools.

Responsibilities

Developing, maintaining, and testing data pipelines to transform data from various structured and unstructured data sources.
Developing complex queries to ensure accessibility while optimizing the performance of SQL and NoSQL for big data infrastructure.
Creating and maintaining optimal data pipeline architecture to support extraction, transformation, and loading (ETL) of data from a wide variety of sources.
Extracting data from multiple sources, including relational SQL and NoSQL databases and platform APIs, for data ingestion and integration.
Configuring and managing data analytic frameworks using tools such as MongoDB, Cassandra, Spark, Hadoop, Kafka, and Hive.
Applying distributed systems concepts and principles including consistency, availability, durability, reliability, and fault-tolerance.
Coordinating with stakeholders and design teams to assist with data-related technical issues and support infrastructure needs.