Location: Reston, VA Clearance Requirement: TS w/ SCI Eligibility Job Description and Responsibilities: Come join the future of data-driven decision making! At Data Machines we leverage data analytics, DevSecOps, machine intelligence, and data science to engineer solutions for our Federal government, defense, and commercial sponsors to solve real-world, critical mission problems. Data Machines is looking for a motivated and detail-oriented Junior Data Engineer to join our growing Data Engineering team. This is an exciting opportunity for someone early in their career to gain hands-on experience with modern data technologies, contribute to the development of data pipelines, and help drive data-driven decision-making across the organization. This position is full-time on site in Reston, VA. Key Responsibilities: Assist in the design, development, and maintenance of scalable data pipelines and ETL processes
Work with structured and unstructured data from various sources to ingest, clean, transform, and store in appropriate formats
Support the creation and optimization of data models in data warehouses (e.g., Postgres)
Monitor data pipeline performance and troubleshoot issues as needed
Collaborate with data analysts, data scientists, and software engineers to understand data needs
Ensure data quality, integrity, and consistency across all data systems
Maintain documentation for data processes and pipelines
Learn and adapt to new tools, technologies, and best practices in data engineering
Minimum Qualifications: Active TS Clearance with SCI Eligibility
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field
Proficiency in SQL and at least one programming language (e.g., Python)
Familiarity with relational databases and data warehousing concepts
Understanding of ETL concepts and tools
Exposure to workflow orchestration tools like Apache Airflow, NiFi and Kafka
Strong analytical and problem-solving skills
Excellent communication and teamwork abilities
Eagerness to learn and grow in a fast-paced environment
Experience in Jupyter Notebooks, PostgreSQL.
Experience with version control systems (e.g., Git)
Desired Qualifications: Knowledge of data lake technologies and big data tools (e.g., Spark)
Familiarity with containerization tools like Docker
