Data Engineer

Company Overview

For over 25 years, Edgesource Corporation has served as an innovative technology service provider for the Department of Defense (DOD), Department of Homeland Security (DHS), Department of State (DOS), the U.S. Intelligence Community, Law Enforcement, and other federal, state, and commercial clients locally, nationally, and abroad. From providing boutique technical solutions in support of the DOD Counter Unmanned Aerial Systems (CUAS) mission set to addressing the most critical Cybersecurity threats facing our nation as a prime contractor with the DHS Cybersecurity & Infrastructure Security Agency (CISA), a career at Edgesource is an opportunity to do meaningful, interesting, and impactful work.

Position Overview

We are seeking a Data Engineer to work with a small team to build complex data flows for a custom application. Successful candidate will have advanced Python programming skills, familiarity with Java, an understanding of data security, privacy, governance and compliance principles and a demonstrated history of building production data pipelines and ETL workflows at scale.

Job Duties

• Building end-to-end data pipelines leveraging Python
• Using orchestration tools to deploy data pipelines, including configuring and updating Spark Jobs
• Containerizing and deploying applications in cloud environments like AWS
• Working with MySQL and PostgreSQL including performance tuning, schema design, and query optimization for complex, analytical workloads
• Leveraging industry standard tools for code control (Git, IaaC control, etc.)
• Working with data catalogs, tracking data lineage and handling a variety of data formats, including Geospatial
• Using Bash scripting for automation and data processing tasks
• Integrating Al/ML services and models
• Working with stakeholders to understand data requirements, assess feasibility, and design appropriate solutions with minimal oversight
• Leveraging strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks
• Leverage a background in large-scale data migration or platform modernization efforts
• Contribute to data engineering documentation, best practices, and design patterns

Required Qualifications

• Active TS/SCI Full Scope Polygraph
• Minimum of 5 years' experience
• Demonstrated experience building production data pipelines and ETL/EL workflows at scale
• Proficiency with Apache Spark and PySpark for distributed data processing
• Advanced Python programming skills including data manipulation libraries (Pandas, NumPy) and data engineering best practices
• Understanding of data security, privacy, governance, and compliance principles
• Experience with workflow orchestration tools (such as Step Functions, Airflow) and containerization (such as Docker or Podman)
• Familiarity with deploying data applications in cloud environments (AWS services: S3, Lambda, Step Functions)
• Experience with AWS services (S3, Lambda, Step Functions)
• Experience with PostgreSQL and MySQL in production environments, including performance tuning and schema design
• Experience with SQL and query optimization for complex analytical workloads
• Experience with version control (Git) and Cl/CD practices for data pipelines
• Demonstrated ability to work with stakeholders to understand data requirements, assess feasibility, and design appropriate solutions with minimal oversight
• Strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks

Nice to Have Qualifications

• Experience with data Lakehouse architecture using Apache Iceberg
• Hands-on experience configuring, deploying, and integrating data platform components: Apache Ranger (access control and data governance), Trino (distributed SQL query engine), Unity Catalog OSS, Apache Polaris, etc.
• Data catalogs (Unity Catalog OSS, Apache Polaris, etc.)
• Apache Superset (data visualization and dashboarding)
• Proficiency with Bash scripting for automation and data processing tasks
• Familiarity or experience with tracking data lineage and associated tooling such as Open lineage
• Familiarity or experience with Java
• Experience with Infrastructure as Code (Terraform or CloudFormation) for data infrastructure
• Experience integrating Al/ML services and models (translation, OCR, speech-to-text, NLP, language detection, topic modeling), LLMs, and RAG (retrieval-augmented generation) pipelines
• Familiarity with geospatial data processing (H3, PostGIS, or similar)
• Contributions to data engineering documentation, best practices, and design patterns
• Experience with NoSQL databases (DynamoDB, etc.)

Compensation Range

$130K - $145K