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 PySpark • 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 Requirements 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 DevOps 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 Core Competencies 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. Highest-signal resume keywords Data Pipeline Development ETL/ELT Processes Cloud-Based Data Solutions Python Programming AWS or Azure Familiarity ATS Optimization Keywords Hard Skills Python SQL PySpark Data Integration ETL Data Warehousing Data Validation Data Modeling Relational Databases Data Querying Soft Skills Analytical Skills Problem-Solving Troubleshooting Communication Collaboration Certifications & Qualifications AWS Certification Azure Certification Data Engineering Certification Industry Keywords Data Engineering Cloud Computing Healthcare Public Sector Federal Clients Tools & Technologies AWS Azure Git Databricks Power BI Tableau Kibana CI/CD Tools Agile Methodologies DevOps Practices #J-18808-Ljbffr