Senior Data Engineer – Automotive Manufacturing

Overview

Our client, a major automotive manufacturer undergoing large‐scale digital transformation, is seeking a Senior Data Engineer with deep experience in cloud data platforms, distributed processing, and production‐grade data pipelines. This role supports enterprise analytics, connected‐vehicle initiatives, manufacturing operations, and next‐generation mobility programs. You will work across cloud, big data, and modern ELT frameworks using AWS, EMR, Airflow, Spark, Python, DBT, DLT, and Snowflake, ensuring high‐quality, scalable, and reliable data delivery for analytics, ML, and operational insights.

Key Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines using Spark, PySpark, DBT, and DLT.
• Develop distributed data processing workflows on AWS EMR and orchestrate pipelines using Airflow.
• Build and maintain ingestion frameworks leveraging S3, Glue, Lambda, and related AWS services.
• Develop and optimize Snowflake data models, warehouses, and performance‐tuned structures.
• Implement CI/CD automation using GitHub and modern deployment pipelines.
• Collaborate with data architects, analysts, and engineering teams to deliver high‐quality datasets for manufacturing, supply chain, and connected‐vehicle programs.
• Ensure data quality, lineage, governance, and documentation across all pipelines.
• Support semantic modeling and metadata management (experience with semantic models is a plus).
• Troubleshoot production issues, optimize performance, and ensure reliability of data systems.

Required Skills & Experience

• 5–8+ years of experience as a Data Engineer in enterprise environments.
• Strong hands‐on experience with AWS (S3, EMR, Glue, Lambda, IAM, CloudWatch).
• Expertise in Spark and PySpark for large‐scale distributed data processing.
• Experience building orchestration workflows using Airflow.
• Strong programming skills in Python.
• Hands‐on experience with DBT and/or Delta Live Tables (DLT).
• Experience with Snowflake including performance tuning, SQL optimization, and data modeling.
• Proficiency with GitHub, branching strategies, and CI/CD pipelines.
• Experience working with large datasets in manufacturing, automotive, or industrial environments (preferred).
• Understanding of semantic models and enterprise data modeling concepts (nice to have).

Preferred Qualifications

• Experience with connected‐vehicle data, telematics, or manufacturing plant systems.
• Familiarity with real‐time or near‐real‐time data processing.
• Knowledge of data governance, lineage, and cataloging tools.
• Strong communication skills and ability to work with cross‐functional engineering teams.

Education

• Bachelor’s or Master’s degree in computer science, Engineering, Data Science, or related field.