Senior Data Engineer

RESPONSIBILITIES

Kforce has a client that is seeking a Senior Data Engineer in Fort Lauderdale, FL to join a highly collaborative data and analytics team.

Overview

This role is responsible for designing, building, and optimizing scalable data platforms that support enterprise reporting, analytics, and data-driven decision-making. The ideal candidate brings deep expertise in cloud-based data engineering, distributed data processing, and real-time streaming technologies while demonstrating strong leadership and mentoring capabilities.

Responsibilities

• Lead and mentor data engineers, promoting best practices in software development, architecture, and deployment
• Design, develop, and maintain enterprise data lake and data warehouse solutions
• Build scalable data pipelines that process structured and semi-structured data across diverse sources
• Develop and optimize cloud-native data solutions using AWS, Azure, or Google Cloud Platform services
• Architect and support high-performance distributed data processing frameworks for large-scale workloads
• Design and maintain real-time streaming solutions using technologies such as Apache Kafka and Apache Flink
• Collaborate with data architects, analysts, and business stakeholders to deliver reliable and scalable data products
• Monitor, troubleshoot, and optimize data pipelines, processing frameworks, and cloud infrastructure
• Drive continuous improvement initiatives by evaluating and implementing emerging technologies and best practices

REQUIREMENTS:

• 7+ years of experience in Data Engineering or a related field
• Proven experience leading, mentoring, or guiding data engineering teams
• Strong experience building and maintaining enterprise data lakes and data warehouses
• Expertise designing and implementing scalable ETL/ELT and data integration solutions
• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
• Experience with cloud storage and compute services, including solutions such as S3, Azure Blob Storage, Databricks, EC2, or Lambda
• Advanced experience with Apache Spark and distributed data processing frameworks
• Strong knowledge of real-time data processing and streaming technologies, including Kafka and Flink
• Proficiency in Python and SQL
• Experience developing automated data workflows and large-scale data transformation processes
• Strong analytical, troubleshooting, and communication skills

Preferred Qualifications

• Experience developing Delta Lakehouse solutions using Databricks
• Expertise optimizing Apache Spark performance through partitioning, caching, tuning, and troubleshooting
• Working knowledge of Java
• Experience supporting low-latency, high-throughput data environments
• Familiarity with modern data architecture patterns and cloud-native platforms
• Passion for emerging technologies and continuous innovation in data engineering

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.

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