Data Engineer

Overview We are seeking an experienced Data Engineer with strong AWS expertise to join our growing data and cloud engineering team. The ideal candidate will design, build, and optimize scalable data pipelines and cloud-native data solutions that support analytics, reporting, and advanced data science initiatives. This role requires hands-on experience with AWS services, modern data engineering tools, and relational databases, along with the ability to collaborate closely with cross-functional teams. Key Responsibilities Design, develop, and deploy end-to-end data pipelines using Python, SQL, and cloud-native services Build and manage ETL/ELT workflows using COTS and GOTS tools across on-prem and AWS environments Develop and optimize data models and manage large datasets stored in AWS services such as S3 and Redshift Write and optimize complex SQL queries for data extraction, transformation, and integration Develop and maintain APIs and web services to support data access and integration Collaborate with business and technical stakeholders to translate requirements into scalable technical solutions Support data visualization and reporting using tools such as Tableau and Power BI Troubleshoot and optimize data workflows for performance, reliability, and scalability Contribute to cloud architecture and IaaS deployments on AWS Support distributed data processing and migration efforts using Apache Spark, Databricks, and related technologies Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field 5+ years of experience in data engineering, data science, or related engineering roles Strong proficiency in Python and SQL; experience with Java and/or R is a plus Hands-on experience with AWS services, including S3, Redshift, and compute services Experience designing and implementing data pipelines and data architectures Strong experience with relational databases such as PostgreSQL, Oracle, MySQL, and Redshift Experience developing RESTful APIs and web services Familiarity with containerization and modern cloud-native development practices Excellent analytical, problem-solving, and communication skills Must be eligible for a Public Trust Preferred Qualifications Experience with machine learning pipelines, model integration, or model deployment Experience porting analytical workloads (SAS, Python, R) to Spark, MapReduce, or multiprocessing environments Solid understanding of data architecture, distributed computing, and core computer science concepts Experience with Databricks and big-data ecosystems Job Details Employment Type: Full-time Work Schedule: Monday–Friday, 9:00 AM – 5:00 PM EST Work Location: Hybrid – 2 days onsite (Reston, VA) and 3 days remote Pay: $95,000.00 - $110,000.00 per year Benefits: 401(k) Dental insurance Flexible schedule Health insurance Paid time off Vision insurance Application Question(s): Are you eligible for a Public Trust? Work Location: Hybrid remote in Reston, VA 20190