Data Engineer

Kforce has a client that is seeking a Data Engineer that will design, build, and maintain scalable data pipelines and core data workflows using AWS-native services including Redshift, Glue, S3, Step Functions, and the Glue Data Catalog. This is a hybrid role in Pittsburgh, PA. Summary: You will own data ingestion, transformation, and validation processes and will be responsible for delivering reliable, well-modeled datasets that support analytics and application use cases. You will collaborate closely with engineering, product, and business stakeholders to ensure data is accurate, accessible, and actionable, while helping shape the future state of the data platform. Duties:

• Design, build, and maintain scalable ETL pipelines using AWS Glue, Crawlers, Apache Hudi, and Step Functions
• Manage and optimize data storage and organization in Amazon S3
• Participate in data modeling and transformation in Amazon Redshift to support analytics, reporting, and downstream applications
• Own metadata management and schema discovery using AWS Glue Data Catalog
• Ensure data quality, integrity, and consistency across all pipelines and datasets
• Develop data access controls and governance practices to ensure secure and appropriate data use
• Implement monitoring, logging, and alerting for data workflows
• Partner with engineering and business teams to define data requirements and deliver trusted datasets
• Enable analytics and reporting through well-documented, well-modeled, and reliable data assets
• Establish best practices for data engineering, documentation, naming conventions, and governance
• Contribute to the roadmap and evolution of the data platform as the organization scales
• Perform other data-related responsibilities as needed
• Strong experience with AWS data services including Redshift, Spark, Glue ETL, Glue Crawlers, S3, Step Functions, and Glue Data Catalog
• Solid understanding of data modeling, ETL/ELT patterns, and downstream consumption needs
• Proficiency in SQL and Python with experience working with large, complex datasets
• Experience building and supporting production-grade data pipelines
• Strong analytical skills with the ability to translate business needs into scalable data solutions
• Ability to work independently, take ownership, and build systems from scratch
• High attention to detail with a strong focus on data accuracy and reliability
• Experience with Git-based workflows and version control
• Clear communication skills and the ability to collaborate across technical and non-technical teams
• Structured, methodical approach to problem solving
• A builder mindset and comfort operating without an established playbook

• Relevant technical certifications
• Experience with AWS EMR, data lakes, and Lake Formation
• Experience coaching engineers or acting in a technical lead capacity
• Background or exposure to data analytics
• Experience working in small or agile teams
• Familiarity with Linux-based environments
• Hands-on experience with Jira and Confluence