Staff Data Engineer

Responsibilities

Kforce has a client in Salt Lake City, UT that is seeking a Staff Data Engineer. Summary: Our partner's Enterprise Technology & Operations team is driving a major modernization effort and seeking a highly experienced Staff Data Engineer to lead the end-to-end migration of on-premise data warehouse systems to modern cloud data platforms (AWS, GCP, or Azure). This role is highly technical, hands-on (80% coding), and central to shaping the future state of our partner's data ecosystem. Key Responsibilities:

• Lead technical strategy, architectural design, and roadmap development for cloud-based data platforms
• Design, build, and optimize scalable data pipelines, workflows, and ELT/ETL processes (Databricks Workflows, Kafka, modern ELT tooling)
• Develop distributed, production-grade solutions using Python, PySpark, and advanced performance-tuning techniques (partitioning, caching, parallelism, efficient data formats)
• Architect and manage cloud-optimized data infrastructure using Databricks on GCP, including cost-efficient Spark workload strategies (right-sizing, autoscaling, serverless, job compute, cluster pools, spot/preemptible workers)
• Build and manage CI/CD pipelines supporting automated testing and deployments
• Design distributed data platforms (data lakes, data warehouses) with strong OLTP/OLAP modeling principles for both real-time and analytical workloads
• Ensure secure data movement and integration between cloud and on-prem environments
• Drive data governance, compliance, and security best practices
• Mentor engineers, lead technical discussions, and coordinate cross-functional efforts
• Produce clear technical documentation and contribute to engineering community initiatives
  
  

Requirements

• 10 years of hands-on data engineering experience; bachelor's or equivalent combination of experience and education
• Significant experience leading full lifecycle migrations from on-prem data warehouses to cloud platforms
• Deep expertise with distributed systems, Python, PySpark, and scalable data architectures
• Strong experience with cloud platforms (GCP preferred), Kubernetes, Docker, and IaC
• Proven success designing cost-optimized Databricks implementations and medallion-style architectures
• Extensive experience supporting both cloud and on-prem environments with secure file/data movement
• Strong communication skills, leadership ability, and experience mentoring engineering teams
• Ability to develop thorough and accurate technical documentation
  
  

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.

Note: 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.

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