Data Engineer
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Job Summary
Role - Data Engineer (Databricks) position.
Location - Tampa FL (Local profiles only)
Please find the JD below :
Job Description Data Engineer (Databricks)
We are seeking a hands-on Data Engineer to join our data platform team and serve as the go-to expert for designing building and scaling modern data solutions.
Role Overview
You will be responsible for building and scaling a cloud-based data platform with a strong focus on Databricks data pipelines and secure architecture. This role combines engineering platform design and data governance with an expectation of ownership from design through implementation.
Key Responsibilities
Design and implement scalable data pipelines for batch and streaming use cases
Build and optimize Databricks-based data platform architecture
Define and implement data models and Lakehouse design patterns
Lead platform scalability performance tuning and cost optimization efforts
Establish and enforce data security access controls and governance standards
Support data ingestion transformation and consumption layers
Enable downstream analytics reporting and AI-driven use cases
Drive best practices for CI/CD automation and operational excellence
Act as the technical SME for data engineering and platform design
Required Skills
Strong experience with Databricks Spark and PySpark
Proven expertise in building data pipelines and distributed data processing systems
Deep understanding of data lake / Lakehouse architectures
Strong SQL and data modeling skills
Experience working with cloud platforms (AWS or equivalent)
Familiarity with data platform design scalability and performance optimization
Nice to Have
Experience with streaming data frameworks
Exposure to AI/ML or data-driven applications
Experience with data governance lineage and security frameworks
Familiarity with CI/CD pipelines for data engineering
What Success Looks Like
Establishes a scalable and secure data platform foundation
Becomes the go-to expert for data engineering and Databricks
Enables faster delivery of data products analytics and AI capabilities
Drives consistent best practices across pipelines architecture and governance
