Data Engineer

About the role

Come Drive Innovation with Us. We are currently looking for a Data Engineer to join our team in Franklin, TN.

Responsibilities

• Design, build, and maintain data pipelines (batch and streaming)
• Ingest data from multiple source systems
• Transform and optimize data for analytics and BI
• Ensure data quality, reliability, and performance
• Implement data pipeline monitoring and alerting
• Collaborate with Data Scientists and BI teams
• Support MLOps and analytics workloads
• Document AI for extracting answers, parsing documents, and summarizing unstructured files.
• Cortex Search & Knowledge Extensions for retrieval-augmented generation (RAG).
• Cortex Agents & Analyst for conversational analytics and autonomous workflows.

Requirements

• Bachelor's Degree in Computer Science, Data Science, or related field required. Master's degree preferred.
• Min 6 years of experience in data engineering required. Automotive industry experience preferred.
• Advanced SQL skills and proficiency in Python and Snowflake required.
• Hands-on experience with creating data models, database design, and data sets required.
• Excellent negotiation and cross-functional skills are required to effectively balance priorities from various functional groups.
• Strong analytical, presentation and strategic thinking skills
• Experience with AWS, and other cloud platforms preferred.

Skills & Experience

• Programming: Python & SQL
• Data platforms (Snowflake, Databricks, BigQuery, Redshift)
• ETL/ELT tools (ADF, Airflow, dbt)
• Streaming technologies (Kafka, Event Hubs)
• DevOps and CI/CD principles

Benefits

Be supported with a Comprehensive Benefits Package, including medical, mental health, parental leave, retirement savings & unique Nissan perks, including discounts on lease vehicles as part of our Employee Lease Program and a Vehicle Purchase Program (VPP).

Pay

Nissan will consider qualified candidates with arrest or conviction records for employment in a manner consistent with these laws.

Schedule

Full time, hybrid (M-TH onsite, F remote)