Job Description

Salary: $100,000 - 140,000 per year Requirements:

• Bachelors degree in Computer Science, Information Systems, Data Engineering, or a related discipline, plus at least 7 years of data engineering experience, including 2 or more years leading engineering initiatives or enterprise-system architecture.
• Demonstrated experience integrating common enterprise systems through database connectors or APIs.
• Hands-on knowledge of data lakehouse architecture and the tradeoffs among data modeling approaches.
• Advanced ability to write optimized, complex SQL queries and manage relational database schemas.
• Experience with modern cloud data platforms, data transformation tools, and code-based orchestration tools such as Apache Airflow, Dagster, or Prefect.
• Experience using software development tools such as Azure DevOps or GitHub for CI/CD and data infrastructure version control.
• U.S. citizenship.
• Preferred: Proficiency in Python and PySpark for engineering, data manipulation, API use, and automation.
• Preferred: Experience with Informatica for API and database extraction.
• Preferred: Experience implementing automated data quality, monitoring, and lineage tools such as Monte Carlo, Great Expectations, Soda, or Databricks Unity Catalog.
• Preferred: Experience building pipelines for machine learning, natural language processing, or vector database/RAG workflows.
• Preferred: Experience with Docker and infrastructure-as-code tools such as Terraform or CloudFormation.
• Ability to remain stationary for 50% of the time, occasionally move around the office, and communicate accurately with colleagues, managers, and customers, including during presentations.

• Design, build, and maintain secure, scalable ETL/ELT pipelines that connect enterprise systems and APIs to a unified data model.
• Develop and update data warehouse schemas to support changing reporting, analytics, and automation needs.
• Provide subject matter expertise in selecting and implementing next-generation analytics platforms and data engineering tools.
• Lead the transition to a modern data lakehouse and support analytics engineers in implementing a universal semantic data model.
• Establish automated data validation, lineage tracking, and end-to-end observability to maintain data quality and pipeline reliability.
• Support analytics engineers in creating orchestration and alerting that notify business leaders when key performance measures exceed defined thresholds.
• Mentor teammates in modern data engineering practices and design data flows suited to machine learning and AI applications.

• AI
• Airflow
• API
• Azure
• CI/CD
• Cloud
• Data Warehouse
• Databricks
• DevOps
• Docker
• ETL
• GitHub
• Informatica
• Support
• Machine Learning
• Python
• PySpark
• RAG
• SQL
• Terraform
• Unity
• GameDev
• Architect
• Business Intelligence

More:

We are partnering with hackajob to connect professionals with MANTECH. We are seeking a Lead Data Engineer for our Enterprise Data, AI, and Automation team in Herndon, Virginia. This is a hybrid role requiring 2–3 days onsite each week. In this position, you will help turn complex raw data into reliable, standardized information for reporting, AI/ML engineering, and other downstream uses, while helping modernize our legacy data warehouse into a data lakehouse platform.

last updated 42 week of 2026

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