Data Engineer

Kforce’s client in NYC is seeking a highly skilled Data Engineer with strong hands-on experience in Apache Spark/PySpark, AWS EMR, Databricks, and Snowflake. The Data Engineer will be responsible for designing and building scalable, high-volume data pipelines, optimizing distributed data processing workloads, implementing data quality and observability frameworks, and resolving complex performance and production challenges across cloud-based data platforms.

• Strong Data Engineer with deep hands-on expertise in Apache Spark/PySpark, AWS EMR, Databricks, and Snowflake
• To be considered for this position, candidates must have experience in a similar role, or they must possess significant knowledge, experience, and abilities to successfully perform the responsibilities listed
• Relevant education and/or training will be considered a plus

Should be capable of:

• Designing and building high-volume, scalable data pipelines
• Optimizing distributed workloads
• Implementing robust data quality and observability
• Troubleshooting complex performance and production issues across cloud-based data platforms

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.

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