Data Engineer - Databricks

Fintech • Tampa, FL

3h • Hybrid

About The Position

This position is Hybrid in Tampa, FL. We are seeking a Data Engineer with strong Databricks expertise to modernize and scale our Business Intelligence (BI) capabilities. This role will design and build data pipelines, deploy machine learning solutions, and operationalize intelligent analytics to drive decision-making across the organization. The ideal candidate blends data engineering best practices with applied machine learning, MLOps, and AI.

Requirements

• Advanced SQL optimization and complex query design
• Kafka streaming applications and connector development
• Databricks workflow development with medallion architecture
• Data governance implementation and compliance
• Performance tuning for large-scale data processing
• Data security and privacy best practices
• Apache NiFi pipeline development for invoice and PO processing
• Integration with purpose-built data stores (Druid, MongoDB, OpenSearch, Postgres)
• Build and maintain end-to-end ML pipelines for training, deployment, and monitoring of models.
• Design and optimize data architectures for large-scale ML workloads
• Explore and implement LLM-based solutions, RAG architectures, and generative AI for business use cases.
• Cross-functional collaboration with product and engineering teams
• Technical mentoring for junior data engineers
• Analytical thinking for complex data problems
• Stakeholder communication for data requirements
• Process improvement and efficiency focus
• Quality mindset for data accuracy and reliability
• Direct communication with data platform vendors
• Evaluates vendor tools for specific data use cases
• Provides technical feedback on vendor product roadmaps
• Coordinates with vendors for data integration projects
• Bachelor’s/Master’s in Computer Science, Data Engineering, Statistics, or related field.
• 5+ years in data engineering
• 2+ years applying ML in production.

Responsibilities

• End-to-end data pipelines and integrations
• Advanced SQL optimization and complex query design
• Kafka streaming applications and connector development
• Databricks workflow development with medallion architecture
• Data governance implementation and compliance
• Performance tuning for large-scale data processing
• Data security and privacy best practices
• Apache NiFi pipeline development for invoice and PO processing
• Integration with purpose-built data stores (Druid, MongoDB, OpenSearch, Postgres)
• Build and maintain end-to-end ML pipelines for training, deployment, and monitoring of models.
• Design and optimize data architectures for large-scale ML workloads
• Explore and implement LLM-based solutions, RAG architectures, and generative AI for business use cases.
• Cross-functional collaboration with product and engineering teams
• Technical mentoring for junior data engineers
• Analytical thinking for complex data problems
• Stakeholder communication for data requirements
• Process improvement and efficiency focus
• Quality mindset for data accuracy and reliability
• Direct communication with data platform vendors
• Evaluates vendor tools for specific data use cases
• Provides technical feedback on vendor product roadmaps
• Coordinates with vendors for data integration projects

Benefits

• Hybrid Work
• Employer Matched 401K
• Company Paid Medical Insurance Option for Employee and Dependent Children
• Company Paid Dental Insurance for Employee
• Company Paid Vision Insurance for Employee
• Company Paid Long and Short-Term Disability
• Company Paid Life and AD&D Insurance
• 18 Paid Vacation Days a Year
• Six Paid Holidays
• Employee Recognition Programs
• Holiday Bonus
• Incentive Compensation
• Community Outreach Opportunities
• Business Casual Dress Code

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level