Data Engineer II

JOB DESCRIPTION

GM Financial is set to change the auto finance industry and is leading the path of embarking on tech modernization - we have a startup mindset, and preserve our small company culture, in a public company environment with financial stability and intense growth over a decade-plus history. We are data junkies and trust in data and insights to advance our business objectives. We take our goal of zero emission, zero collision, zero congestion, and zero friction very seriously. We believe as an auto finance market leader we are in the driver's seat to lead us in the GM EV mission to change the world. We are building global platforms, in LATAM, Europe, China, U.S. and Canada - and we are looking to grow our high-performing team. GMF is comprised of over 10,000 team members globally. Join our fintech culture within a Blue-Chip company where we are changing the way we use technology to support our customers, dealers and business.

We are seeking a skilled and innovative Data Engineer II to join our team and contribute to the advancement of our data engineering capabilities. This role involves working with cutting-edge technologies in both batch and streaming data environments, supporting the adoption of emerging tools and practices, and collaborating across teams to deliver high-quality data solutions.

RESPONSIBILITIES

• Research, evaluate, and experiment with emerging data engineering technologies in a lab environment to stay ahead of industry trends.
• Collaborate with data engineering teams to demonstrate the capabilities of new technologies and facilitate their adoption.
• Help define and refine processes and best practices for the data engineering discipline.
• Partner with business stakeholders, data architects, ETL developers, reporting teams, data scientists, and IT counterparts to identify and integrate data from various sources including external systems, internal databases, and data warehouses.
• Develop, test, deploy, monitor, and troubleshoot data pipelines and automation processes.
• Maintain comprehensive documentation and ensure reconciliation of data processes.

QUALIFICATIONS

Experience

• Bachelor's degree in related field or equivalent work experience.
• 2-4 years of hands-on experience in data engineering.
• 2-4 years of experience processing large datasets using tools such as Databricks, Python, Spark, Kafka, and APIs.
• Proficiency in ingesting diverse data formats (XML, JSON, Parquet, SequenceFile) and integrating with various data sources (Oracle, cloud databases, Event Hub, Service Bus).
• Experience with cloud platforms (Azure, AWS) and infrastructure automation tools (ARM Templates, Terraform, CloudFormation).
• Strong understanding of cloud computing models (IaaS, PaaS, SaaS) and hybrid cloud environments.
• Familiarity with object storage technologies (Data Lake Storage Gen2, Blob, S3, ADLS).
• Experience with Agile/Scrum methodologies and application lifecycle management.
• Proficient in source control (Git), CI/CD pipelines (Azure DevOps), and artifact repositories (Artifactory).
• Experience creating and maintaining ETL processes.
• Knowledge of IT governance, privacy compliance, and GDPR.
• Preferred experience with Adobe Experience Platform, REST APIs, IBM Infosphere (Datastage), and Unix scripting.

What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.

Our Culture: Our team members define and shape our culture - an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work - we thrive.

Compensation: Competitive pay and bonus eligibility

Work Life Balance: Flexible hybrid work environment, minimum of 2-days a week in office

#LI-hybrid

#LI-MH1

#GMFJobs

Client-provided location(s): Detroit, MI, Arlington, TX

Job ID: GM_Financial-450

Employment Type: FULL_TIME

Posted: 2025-08-15T19:28:22