<p>Kforce is working with a client that is seeking a Senior Data Engineer to help architect, build, and support modern data platforms on AWS. This position is onsite, 5 days a week in downtown Saint Louis, MO.</p> <p>Summary: In this role, you'll design and optimize data pipelines that power analytics, reporting, and data-driven decision-making across the organization. You'll work with large, complex data sets while ensuring data is accurate, secure, and readily available for downstream use. This position plays a key role in translating business needs into scalable, cloud-based data solutions.</p> <p>Duties:</p> <ul> <li>Senior Data Engineer will design, develop, and support robust data pipelines that move data from diverse source systems into AWS-based platforms </li><li>Partner with business and technical stakeholders to gather requirements and deliver data solutions aligned to organizational needs </li><li>Implement and maintain ETL/ELT processes that transform raw data into high-quality, analytics-ready datasets </li><li>Monitor pipeline performance, proactively troubleshoot issues, and continuously optimize for reliability and scalability </li><li>As a Senior Data Engineer, you will ensure strong data quality, consistency, and integrity across all data assets </li><li>Apply best practices for data security, privacy, and governance throughout the data lifecycle* Bachelor's degree in Computer Science or a related field, or equivalent practical experience </li><li>10+ years of progressive experience in data engineering or related roles </li><li>Deep experience with AWS data services, including S3, Redshift, Aurora PostgreSQL, Glue, Lambda, Step Functions, Lake Formation, DataZone, Kinesis, MSK, and EMR </li><li>Hands-on experience with relational databases (e.g., PostgreSQL, SQL Server) and distributed data processing frameworks such as PySpark </li><li>Proven experience building and managing ETL pipelines using tools like AWS Glue and SSIS </li><li>Experience integrating multiple data sources while maintaining data accuracy and consistency </li><li>Solid understanding of data modeling, schema design, and database architecture </li><li>Familiarity with data orchestration and workflow tools such as Apache Airflow, Glue Workflows, and AWS Step Functions, including alerting and notifications </li><li>Exposure to Infrastructure as Code and DevOps practices (e.g., Terraform, Git, CI/CD pipelines) </li><li>Working knowledge of data governance, regulatory requirements, and security best practices </li><li>Strong analytical and problem-solving skills, with the ability to diagnose complex data issues and recommend solutions </li></ul> <p>Technologies:</p> <ul> <li>Languages: Python, SQL </li><li>AWS Services: Glue, S3, Redshift, Lambda, Lake Formation, DataZone </li><li>Strong proficiency in Python and SQL for data transformation, querying, and automation </li></ul>