Data Engineer- AI ML

Project Responsibility: End-to-end data pipelines and integrations

Technical Competencies:

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 Vendor Management:

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

Qualifications:

Bachelor's/Master's in Computer Science, Data Engineering, Statistics, or related field.

5+ years in data engineering; 2+ years applying ML in production.

Pulled from the full job description

• Professional development assistance
• 401(k)
• Health insurance
• Retirement plan
• Paid time off
• Vision insurance
• Dental insurance, * 401(k)
• Dental insurance
• Flexible schedule
• Health insurance
• Life insurance
• Paid time off
• Professional development assistance
• Retirement plan
• Vision insurance