Job Description

Job Title: Lead Data Platform Engineer

Location: Miramar, FL/ Dallas, TX

Contract

Summary

Are you passionate about building and supporting modern data platforms in the cloud? We're looking for a Sr. Data Platform Engineer who thrives in a hybrid role-60% administration and 40% development/support-to help us scale our data and DataOps infrastructure. You'll work with cutting-edge technologies like Databricks, Apache Spark, Delta Lake, and AWS CloudOps, Cloud Security, while supporting mission-critical data pipelines and integrations. If you're a hands-on engineer with strong Python skills, deep AWS experience, and a knack for solving complex data challenges, we want to hear from you.

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines and integration frameworks.
• Administer and optimize Databricks and Apache Spark environments for data engineering workloads.
• Build and manage data workflows using AWS services such as Lambda, Glue, Redshift, SageMaker, and S3.
• Support and troubleshoot DataOps pipelines, ensuring reliability and performance across environments.
• Automate platform operations using Python, PySpark, and infrastructure-as-code tools.
• Collaborate with cross-functional teams to support data ingestion, transformation, and deployment.
• Provide technical leadership and mentorship to junior developers and third-party teams.
• Create and maintain technical documentation and training materials.
• Troubleshoot recurring issues and implement long-term resolutions.

Minimum Qualifications

• Bachelor's or Master's degree in Computer Science or related field.
• 5+ years of experience in data engineering or platform administration.
• 3+ years of experience in integration framework development with a strong emphasis on Databricks, AWS, and ETL.

Required Technical Skills

• Strong programming skills in Python and PySpark.
• Expertise in Databricks, Apache Spark, and Delta Lake.
• Proficiency in AWS CloudOps, Cloud Security, including configuration, deployment, and monitoring.
• Strong SQL skills and hands-on experience with Amazon Redshift.
• Experience with ETL development, data transformation, and orchestration tools.

Nice to Have / Working Knowledge

• Kafka for real-time data streaming and integration.
• Fivetran and DBT for data ingestion and transformation.
• Familiarity with DataOps practices and open-source data tooling.
• Experience with integration tools such as Apache Camel and MuleSoft.
• Understanding of RESTful APIs, message queuing, and event-driven architectures.

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