Data Engineer

Nissan Motor Corporation•Franklin, TN

1d•Hybrid

About The Position

The Data Engineer builds and maintains reliable, scalable data pipelines that make data available for analytics, reporting, and data science. This role involves designing, building, and maintaining data pipelines (batch and streaming), ingesting data from multiple source systems, transforming and optimizing data for analytics and BI, and ensuring data quality, reliability, and performance. The Data Engineer will also implement data pipeline monitoring and alerting, collaborate with Data Scientists and BI teams, and support MLOps and analytics workloads. Specific technologies mentioned include Cortex Search & Knowledge Extensions for retrieval-augmented generation (RAG), and Cortex Agents & Analyst for conversational analytics and autonomous workflows.

Requirements

Bachelor’s Degree in Computer Science, Data Science, or related field required.
Min 6 years of experience in data engineering required.
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
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
Pipeline reliability and uptime
Data freshness / latency
Data quality error rates
Cost efficiency of data processing
Legally authorized to work in the United States and will be required to provide proof of employment eligibility at the time of hire; Nissan uses E-Verify to validate employment eligibility.

Nice To Haves

Master’s degree preferred.
Automotive industry experience preferred.
Experience with AWS, and other cloud platforms preferred.

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.
Data ingestion and transformation pipelines
Curated datasets / data marts
Automated workflows and jobs
Monitoring and logging for pipelines
Documentation of data flows