AWS Data Engineer

Job Information Date Opened 09/09/2025 Job Type Contract Industry Banking Work Experience 8 + years Salary $50/Hr on C2C City Richmond State/Province Virginia Country United States Zip/Postal Code 23173 About Us At Appex Innovations, we believe in the power of technology to transform healthcare, we believe in being nimble and in continual innovation, we believe that every customer is unique and we believe in listening to our clients. With our deep expertise in the health care domain, solid resource base, constant industry interface and the drive to be the best in the industry, we strive to provide services that re-define health care in the years to come. The secret to our success is Appex Innovations commitment to our people and our work. We thrive on teamwork, intelligence, and innovation. Our bright and energetic employees, hailing from over different parts of the world, share a passion for leading the way to improved healthcare outcomes. Together we work diligently to add value to our clients. Job Description We are hiring for AWS Data Engineer for our client based in Richmond, VA. Job Details: Role: Data Engineer Skills Required: Python, AWS, PySpark Openings: 10 positions Location: Richmond, VA, (Onsite) Client/Domain: Banking Domain Interview Process: Candidates must be available for in-person interviews at one of the following locations: McLean, VA Richmond, VA Dallas, TX Job Description: We are seeking a skilled and motivated Data Engineer to join our team in Richmond, VA. The ideal candidate will have a strong background in building and maintaining data pipelines and be proficient in the following technologies: Required Skills: Python: Strong programming skills for data manipulation, scripting, and automation. AWS: Experience with various AWS services (e.g., S3, EC2, Lambda, Glue, Redshift, etc.). PySpark: Hands-on experience with PySpark for big data processing and ETL jobs. Domain Knowledge: Previous experience working in the Banking or Financial Services domain is highly preferred. Key Responsibilities: Design, develop, and maintain scalable and efficient data pipelines. Collaborate with data scientists and analysts to support their data needs. Ensure data quality, reliability, and security. Optimize data processing jobs for performance.