Data Integration Engineer

Swarmint•Bethesda, MD

19h•Onsite

About The Position

We need a Data Integration Engineer to build robust pipelines for a large-scale enterprise data solution supporting our Intelligence Community customer. You'll architect data flows that move petabytes of information from diverse sources into unified intelligence platforms. This role requires regular on-site work at customer facilities in Bethesda, Maryland, including work in classified facilities (SCIF).

Requirements

Bachelor's degree in Computer Science, Data Engineering, or related field
8-12 years experience building data pipelines and integration systems
Experience with Elasticsearch or similar search technologies
Strong programming skills with experience in data processing
Experience with data pipeline orchestration and workflow management
Proficiency with databases and data modeling
Understanding of streaming data concepts and architectures
Experience with APIs and data serialization
Strong experience with containerization technologies (Docker)
Active TS/SCI with Single Scope (CI) Polygraph Required (Do not apply unless you have this)
U.S. Citizenship required
Ability to work on-site in Bethesda, Maryland 2-4 days/week including at classified facilities

Nice To Haves

Experience with video streaming protocols and real-time data feeds
Knowledge of geospatial data formats and processing
Familiarity with defense data standards and military protocols
Experience with distributed streaming platforms
Proficiency with workflow orchestration frameworks
Experience with time-series databases and analytics
Knowledge of data transformation tools and frameworks
Understanding of ML data pipelines and feature engineering
Knowledge of message queuing and pub/sub systems
Experience with infrastructure automation tools
Knowledge of government data systems and security requirements (NIST 800-171, CMMC)
Experience in air-gapped or restricted environments
Experience with enterprise-scale data solutions at petabyte scale

Responsibilities

Design and implement data pipelines integrating diverse sources
Build real-time streaming architectures for data ingestion and processing
Develop ETL/ELT workflows for transforming and standardizing multi-source data
Create data connectors for military and government data formats and protocols
Implement data quality monitoring, validation, and anomaly detection
Build APIs and services for efficient data access and distribution
Architect data flows across distributed systems
Optimize pipelines for performance, reliability, and fault tolerance in challenging network conditions
Orchestrate complex workflows and manage data dependencies
Document data schemas, lineage, and integration architecture
Deploy and manage data infrastructure using containerized deployments
Collaborate with AI/ML teams to prepare and deliver data for training and inference