Staff Data Engineer, Commercial Software

Job Description

Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to Mountain View three times per week, at minimum.

The Role

The Commercial Software division at GM is seeking talented individuals across various software engineering roles to join us. Our mission? Driving forward all digital solutions for commercial fleet owners and drivers, catering to businesses of all sizes, from small and medium businesses to large enterprises.

In today's dynamic landscape, the demand for intelligent, safe, and eco-friendly transportation solutions is skyrocketing. GM is at the forefront of this transformative journey, championing connected software-defined vehicles that redefine the driving experience. At the heart of this paradigm shift lies software – enabling seamless communication, bolstering security, facilitating updates, processing data, and ultimately, delivering an unparalleled user experience. These capabilities extend beyond consumer benefits, holding even greater significance for business owners.

Recognizing this pivotal moment, GM has recruited a significant number of big tech engineering, product, and leaders to lead the GM Software & Services organization. As a leading OEM with a vast fleet of vehicles spanning the globe, we're uniquely positioned to leverage our comprehensive control over in-vehicle and cloud software. Our aim? Seamlessly integrating solutions such as fleet management, energy optimization, transportation logistics, safety systems, and more, all geared towards enhancing efficiency and sustainability.

To realize our vision, we're actively expanding our software teams in the Bay Area. We seek individuals who can blend a passion for technology and sustainability with curiosity, rigorous thinking and a strong customer centric approach. This is an exceptional opportunity where you can leverage the scale of GM and make a significant impact and find fulfillment in crafting innovative software solutions. We invite you to join us on this exciting journey toward a better future.

What You'll Do

As a Staff Data Engineer, you will be responsible for designing, developing, and maintaining efficient data workflows and associated cloud infrastructure that support GM Commercial Software’s core analytic products and services. A key focus of this role will be on developing and optimizing streaming data pipelines, ideally utilizing Spark or similar technologies. You will work closely with our data scientists, DevOps, and software engineers to automate pipelines that process streaming vehicle telemetry data, ensuring real-time data processing and transformation. Additionally, you will transform data within our data lakehouse into deployable data models that power our automated fleet insights, visualizations, and emerging machine learning, optimization, and AI applications. The ideal candidate will have extensive experience in setting up ELT pipelines to handle massive volumes of spatiotemporal data, designing enterprise data warehouse models, implementing robust data quality tests, and leveraging data pipeline-as-code integration systems. Your expertise in streaming data technologies will be crucial for ensuring the smooth and efficient orchestration of the workflows that power our advanced analytics platform.

Additional Job Description

Your Skills & Abilities (Required Qualifications)

• Bachelor's Degree or equivalent experience in computer science, data science, engineering, or related quantitative field 

• 7+ years of industry experience developing, implementing, and maintaining solutions for Big Data or data warehousing systems

• 5+ years of industry experience working in a cloud environment (Azure preferred)

• 5+ years' experience working with SQL query authoring for automated data transformation (familiarity with dbt preferred, but not required).

• 3+ years of experience developing streaming data processing pipelines (use of Spark/pySpark preferred)

• Basic understanding of machine learning/statistical learning principles

• Experience implementing and maintaining data workflow orchestration and integration tools (e.g.  Airflow/Astro, Prefect, dbt cloud, etc.)

• Understanding of and experience with application of data quality tools integrated with CI/CD automation frameworks in functional deployment environments (e.g., Github Actions/Azure DevOps pipelines).

• Familiarity with data quality testing frameworks (Great Expectations, Deequ)

• Self-driven with an interest in on-t