Data Engineer
US$130,000 – US$170,000 / yr base salary
Posted 18 Aug 2026
Advertised as “Senior Data Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 4–7 yrs
- Management level
- People management
- Contract
- Full-time
| Base salary | US$130,000 – US$170,000 / yr |
|---|
Field of studyComputer Science, Engineering, Information Systems (or related)
Study levelBachelor's
CertificationsAWS Certified Data Engineer, Databricks Certified Data Engineer, CKA
Study levelMaster's
Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission’s biggest challenges.
Dark Wolf is seeking a Senior Data Engineer to design, build, and optimize robust data pipelines, data warehouses, and streaming solutions. You will be responsible for integrating heterogeneous data sources, building complex analytical data models, automating workflows, and deploying containerized data services within multi-cloud secure environments.
Key Responsibilities
- Design and implement batch and real-time streaming data ingestion pipelines utilizing Spark, Kafka, and Airflow.
- Model and build performant data structures within enterprise data warehouses (e.g., Snowflake, Redshift, BigQuery).
- Deploy and manage containerized data microservices using Docker and Kubernetes.
- Integrate automated security scanning and credential management tools into continuous integration (CI/CD) data pipelines.
- Collaborate within Agile teams to estimate user stories, review code, and mentor junior data engineers.
Qualifications:
- Clearance: Must be a US Citizen holding an active TS/SCI security clearance with an active Full-Scope Polygraph.
- Education: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field (Master’s degree preferred).
- Experience: 4-7+ years of data engineering experience.
Technical Competencies:
- Data Processing Frameworks: Hands-on experience with PySpark, Apache Airflow, Kafka, and dbt.
- Database Systems: Strong expertise with MPP databases, distributed data stores, and graph or key-value engines.
- Data Modeling: Proficiency in Kimball dimensional modeling, Data Vault 2.0, and high-performance schema optimization.
- Programming & Scripting: Strong proficiency in Python, SQL, Scala, or Java, alongside REST API development.
- Containerization: Proficient with Docker container orchestration, Kubernetes deployment, and Helm charts.
- Agile Frameworks: Active participation in Agile sprint execution, story point estimation, and backlog grooming.