We are seeking a
Data Engineer to help build and scale the data foundation for our
Vehicle Configuration Optimization (VCO) initiative. This role will focus on ingesting, transforming, and structuring data from enterprise systems (e.g., Snowflake data lake) into
Databricks, enabling advanced analytics and modeling downstream.
This is an ideal role for an
early-to-mid career engineer who thrives in building reliable, scalable data systems and wants to work at the intersection of automotive data and advanced analytics.
Key Responsibilities:- Build and maintain data pipelines that ingest data from Snowflake into Databricks
- Design and implement data transformations aligned to the medallion architecture (Bronze/Silver/Gold layers)
- Ensure pipeline health, stability, monitoring, and performance optimization
- Develop robust ETL/ELT workflows using Python and SQL
- Create clean, curated datasets to support analytics, simulation, and machine learning use cases
- Partner closely with data scientists, analysts, and business stakeholders to understand data needs
- Implement data quality checks, validation processes, and governance standards
Basic Qualifications:- Minimum 5 years of experience in data engineering or similar role
- Bachelors Degree
- Strong hands-on experience with Databricks (critical requirement)
- Proficiency in SQL and Python
- Experience building and maintaining data pipelines and ETL processes
- Familiarity with cloud data platforms (Azure preferred, but AWS/GCP acceptable)
- Solid understanding of data modeling and medallion architecture concepts
Preferred Qualifications:- Experience with Snowflake and data lake architectures
- Exposure to automotive, connected vehicle, or IoT datasets
- Experience with Spark / PySpark
- Familiarity with pipeline orchestration and monitoring tools
Understanding of downstream analytics or ML use cases
