Data Engineer - AI/ML

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

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