Data Engineer

Responsibilities 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 Requirements 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 Preferred Qualifications 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 The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future. We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave. Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law. This job is not eligible for bonuses, incentives or commissions. Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status. #J-18808-Ljbffr