Senior Data Engineer

We are seeking a highly skilled Sr Data Platform Engineer to join our team in Long-Term Contract, Hybrid role in Dallas, TX or Miramar, FL. 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. 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. Requirements: • 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. • Strong AWS: fundamental understanding of cloud trail, cloud watch, S3, and ML platform experience (Glue, Lambda, AWS console management) • Experience managing Databricks on AWS platform and integrating with Redshift and Databricks • 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. • 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.