Data Engineer

• Assist in developing, testing, and maintaining data pipelines and ETL/ELT processes that ingest, transform, and load data from various sources

• Support the implementation and enhancement of data models, databases, and cloud-based data solutions

• Participate in data integration, migration, and modernization initiatives under senior engineer guidance

• Develop and maintain scripts, queries, and applications using Python, SQL, and Py Spark

• Support cloud-based data environments and services in AWS and Azure

• Assist with CI/CD processes and software development best practices using Git and related tools

• Monitor data pipelines and systems, identify issues, and support troubleshooting and resolution

• Perform data validation and quality assurance activities

• Collaborate with data engineers, developers, analysts, and stakeholders to deliver solutions

• Document technical processes, data flows, and system configurations

• Continuously develop technical skills and stay current with data engineering technologies and best practices

• Must be able to obtain and maintain a Federal or DHS Public Trust
• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or a related technical field
• Experience in data engineering, software engineering, data analytics, computer science, or a STEM-related technical discipline
• Foundational knowledge of Python, Java, or SQL
• Basic understanding of relational databases and data querying concepts
• Familiarity with AWS or Azure through coursework, certifications, internships, or professional experience
• Exposure to data integration, ETL, data warehousing, or analytics concepts
• Internship, academic, research, or project experience involving data engineering, cloud computing, or software development is nice to have
• Exposure to Databricks, Spark, or large-scale data processing technologies is nice to have
• Familiarity with Git is nice to have
• Basic understanding of software development lifecycle and Agile methodologies is nice to have
• Strong analytical, problem-solving, troubleshooting, communication, and collaboration skills
• Familiarity with AWS services such as S3, Lambda, or Redshift, or Azure services such as Azure Data Factory, Azure Functions, or Cosmos DB is nice to have
• Experience with Power BI, Tableau, or Kibana is nice to have
• Exposure to CI/CD tools and Dev Ops practices is nice to have
• AWS, Azure, Databricks, or related cloud/data certifications are nice to have
• Experience supporting healthcare, public sector, or federal clients is nice to have
• Interest in data architecture, machine learning, artificial intelligence, or advanced analytics is nice to have
• Previous consulting, client-facing, internship, or cooperative education experience is nice to have

Demonstrates expertise in developing and maintaining data pipelines, ETL/ELT processes, and cloud-based data solutions using Python, SQL, and AWS or Azure. Strong analytical and problem-solving skills are essential for troubleshooting and ensuring data quality.

• Data Pipeline Development
• ETL/ELT Processes
• Cloud-Based Data Solutions
• Python Programming
• AWS or Azure Familiarity

• Python
• SQL
• Py Spark
• Data Integration
• ETL
• Data Warehousing
• Data Validation
• Data Modeling
• Relational Databases
• Data Querying

• Analytical Skills
• Problem-Solving
• Troubleshooting
• Communication
• Collaboration

• AWS Certification
• Azure Certification
• Data Engineering Certification

• Data Engineering
• Cloud Computing
• Healthcare
• Public Sector
• Federal Clients

• AWS
• Azure
• Git
• Databricks
• Power BI
• Tableau
• Kibana
• CI/CD Tools
• Agile Methodologies
• Dev Ops Practices