Data Engineer: Pipelines, ETL & Big Data Systems

MANTECH; United States; On-site; USD 90,000 - 150,000; Full time

Job summary

MANTECH is seeking a motivated Data Engineer to join our team in the United States. The role focuses on building and refining data pipelines, optimizing performance, and enabling reliable data distribution for downstream users.

Candidates should have hands-on experience with SQL/NoSQL, distributed computing, and API-driven architectures, along with strong documentation skills and Agile practices. A Secret clearance is preferred where applicable.

Qualifications

• Bachelor’s degree in a STEM field as a baseline requirement.
• Experience with data structures, databases, distributed computing, and APIs.
• Familiarity with Agile practices and Git operations.
• Ability to document complex data systems clearly.

Responsibilities

• Develop, maintain, and test data pipelines from diverse sources.
• Write complex SQL/NoSQL queries and optimize for big data infra.
• Design and maintain ETL pipelines to support data ingestion.
• Extract data from SQL/NoSQL sources and platform APIs for integration.
• Configure analytics frameworks such as MongoDB, Cassandra, Spark, Hadoop, Kafka, Hive.
• Apply distributed systems concepts including fault tolerance and reliability.
• Collaborate with stakeholders to address data-related issues and needs.

Skills

Data pipelines

SQL

NoSQL

Distributed computing

Agile development

Git

API-driven architectures

Technical documentation

Education

BSc in STEM

Tools

MongoDB

Cassandra

Spark

Hadoop

Kafka

Hive

Job description

MANTECH is seeking a motivated Data Engineer to join our team in the United States. The role focuses on building and refining data pipelines, optimizing performance, and enabling reliable data distribution for downstream users.

Candidates should have hands-on experience with SQL/NoSQL, distributed computing, and API-driven architectures, along with strong documentation skills and Agile practices. A Secret clearance is preferred where applicable.