Data Engineer - Databricks
Fintech•Tampa, FL
•Hybrid
About The Position
Fintech is seeking a Data Engineer with strong Databricks expertise to modernize and scale its Business Intelligence capabilities. The role designs and builds data pipelines, deploys machine learning solutions, and operationalizes intelligent analytics to support decision-making across the organization. The ideal candidate combines data engineering best practices with applied machine learning, MLOps, and AI. The position is hybrid in Tampa, Florida.
Requirements
- Bachelor’s or master’s degree in Computer Science, Data Engineering, Statistics, or a related field.
- At least 5 years of experience in data engineering.
- At least 2 years of experience applying machine learning in production.
- Strong Databricks expertise.
- Advanced SQL optimization and complex query design skills.
- Experience with Kafka streaming applications and connector development.
- Experience developing Databricks workflows with medallion architecture.
- Experience with data governance, compliance, security, and privacy best practices.
- Experience tuning performance for large-scale data processing.
- Experience developing Apache NiFi pipelines for invoice and purchase order processing.
- Experience integrating with Druid, MongoDB, OpenSearch, and Postgres.
- Ability to build and maintain machine learning pipelines and optimize architectures for large-scale ML workloads.
- Analytical thinking, cross-functional collaboration, stakeholder communication, process improvement, and a quality mindset.
Responsibilities
- Design and build end-to-end data pipelines and integrations.
- Optimize SQL queries and develop complex queries.
- Develop Kafka streaming applications and connectors.
- Develop Databricks workflows using medallion architecture.
- Implement data governance and compliance practices.
- Tune performance for large-scale data processing.
- Apply data security and privacy best practices.
- Develop Apache NiFi pipelines for invoice and purchase order processing.
- Integrate with purpose-built data stores, including Druid, MongoDB, OpenSearch, and Postgres.
- Build and maintain end-to-end machine learning pipelines for model training, deployment, and monitoring.
- Design and optimize data architectures for large-scale machine learning workloads.
- Explore and implement LLM-based solutions, RAG architectures, and generative AI for business use cases.
- Collaborate with product and engineering teams and communicate data requirements to stakeholders.
- Mentor junior data engineers.
- Improve processes and efficiency while maintaining data accuracy and reliability.
- Communicate directly with data platform vendors, evaluate tools for specific use cases, provide technical feedback on product roadmaps, and coordinate data integration projects.
Benefits
- Hybrid work.
- Employer-matched 401(k).
- Company-paid medical insurance option for the employee and dependent children.
- Company-paid dental insurance for the employee.
- Company-paid vision insurance for the employee.
- Company-paid long- and short-term disability insurance.
- Company-paid life and AD&D insurance.
- 18 paid vacation days per year.
- Six paid holidays.
- Employee recognition programs.
- Holiday bonus.
- Incentive compensation.
- Community outreach opportunities.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
