Data Engineer - Journeyman

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Note: This is a remote position with the ideal candidate residing near one of our office sites in Colorado Springs, CO.;
Dayton, OH.; or Huntsville, AL.

Required Experience Data Warehousing & Analytics (Core Requirement)

• Advanced proficiency in SQL with extensive experience in cloud data warehousing. Must have deep knowledge of data modeling, schema design, and query optimization.
• GCP Preference: Significant, hands‑on experience with Google Big Query (partitioning, clustering, BQ scripting, cost optimization) is essential.

Modern Data Pipeline Expertise (Must-Have Foundation)

• Orchestration: Deep expertise in Apache Airflow (designing, deploying, scaling, and managing complex DAGs).
• GCP Preference: Hands‑on experience with Google Cloud Composer.
• Processing: Proven ability to build and optimize robust, high‑throughput batch and streaming data pipelines using Apache Beam.
• GCP Preference: Direct experience managing Beam pipelines at scale using Google Cloud Dataflow.
• (
  
  Note:
  
  This role offers the flexibility to architect solutions and select the appropriate services to meet project requirements).

Relational Database Expertise (Must-Have Foundation)

• Solid foundation and practical experience with RDBMS architecture, management, and optimization, specifically with Postgre
  
  SQL.
• GCP Preference: Familiarity with managed database services, particularly Google Cloud SQL (for Postgre
  
  SQL or MySQL), is a significant advantage.

Core Programming & Infrastructure

• Fluency in Python (preferred) or Java for data pipeline development.
• Strong understanding of CI/CD, Git, and Infrastructure-as-Code (e.g., Terraform).

Cloud Architecture & GCP (Highly Desirable)

• Broad experience in architecting, building, and managing solutions on a major cloud platform, with a strong preference for Google Cloud Platform (GCP) beyond just its data services.

Containerization & Kubernetes (Highly Desirable)

• Understanding of container concepts (Docker) and practical experience with Kubernetes, particularly Google Kubernetes Engine (GKE).

ML Engineering Exposure (Plus)

• Experience supporting machine learning workflows, including data preparation, feature engineering, and operationalizing data pipelines for ML models.
• GCP Preference: Any exposure to Google Cloud Vertex AI (Pipelines, Feature Store, Training) is a major plus.

Qualifications And Education Requirements

• Bachelor’s or master’s degree in computer science, Data Science, or a related field.
• 5‑8 years of hands‑on experience in data engineering, demonstrating a clear progression in designing, building, and maintaining scalable data‑intensive systems.
• Demonstrated ability to communicate complex data issues to both technical and non‑technical stakeholders.

Travel

Occasional travel to MTSI offices and events throughout the country.

Clearance

Must have a Secret Clearance; US Citizenship required.

Compensation and Benefits

The pay range for this position in Colorado is $105,000/year to $125,000/year; however, base pay offered may vary depending on established government contract rates, job‑related knowledge, skills, and experience, and other factors. MTSI also offers a full range of medical, financial, and other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location.

Applicants should apply via MTSI’s internal or external careers site.

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