Data Engineer - Vehicle Configuration Optimization

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

Requirements:

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