Data Engineer 2

Why GM Financial?

GM Financial is the wholly owned captive finance subsidiary of General Motors and is headquartered in Fort Worth, U.S. We are a global provider of auto finance solutions, with operations in North America, South America, and the Asia Pacific region. Through our long-standing relationships with auto dealers, we offer attractive retail financing and lease programs to meet the needs of each customer. We also offer commercial lending products to dealers to help them finance and grow their businesses.

At GM Financial, our team members define and shape our culture — an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.

Our Purpose:  We pioneer the innovations that move and connect people to what matters.

This position will be posted until filled.

What makes You an ideal candidate?

You're a strong fit if you enjoy solving complex data challenges, working with modern cloud technologies, and building scalable solutions that turn data into meaningful insights. You're comfortable collaborating across teams, learning new technologies, and using AI- enabled tools to work more efficiently. 

• Experience designing, processing, and managing large-scale data using technologies such as Hadoop, Spark, Kafka, HDFS, or similar distributed platforms.
• Hands-on experience with cloud platforms such as Azure, AWS, or Google Cloud, including infrastructure-as-code tools such as Terraform, ARM Templates, or CloudFormation.
• Experience building and maintaining ETL/data pipelines and working with multiple data formats and sources, including JSON, Parquet, relational databases, cloud databases, and messaging platforms.
• Understanding of modern data architectures, including data lakes, lakehouses, streaming pipelines, and object storage technologies such as ADLS Gen2 and Amazon S3.
• Experience with SQL and NoSQL technologies such as Cosmos DB, MongoDB, Cassandra, or Redis, with the ability to analyze data and translate findings into meaningful insights.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with DevOps and software development practices, including Git, CI/CD, build tools, code quality tools, and artifact management.
• Experience with digital data and customer-data technologies such as Adobe Experience Platform, Real-Time CDP, Journey Analytics, tag management platforms, SDKs, and REST APIs.
• Understanding of data privacy, security, governance, and regulatory considerations, including GDPR.
• Experience working in Agile environments using Scrum, SAFe, or similar methodologies.
• Strong problem-solving and troubleshooting skills, with the ability to collaborate across technical and business teams.
• Strong written and verbal communication skills, with the ability to explain technical concepts and data insights clearly.

Additional Knowledge and Skills

Working effectively within an AI enabled environment:  

• Ability to use AI tools (e.g., Microsoft Copilot) to support daily work
• Skills in evaluating AI outputs for accuracy, compliance, and bias
• Experience integrating AI into workflows to improve efficiency or insights
• Familiarity with AI assisted research, summarization, and content generation
• Understanding of responsible AI use, including ethics and data protection 

Work Experience & Education

• 2-4 years of hands-on experience with data engineering required
• High School Diploma or equivalent required
• Bachelor’s Degree in related field or equivalent experience required

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:  Hybrid work environment, 3-days a week in office. (Tuesday, Wednesday, Thursday) 

NOTE: We are unable to consider candidates who require visa sponsorship now or in the future for this position.

This position is not open to agency submissions 

About the role:

This role focuses on designing, integrating, and managing data pipelines that collect, transform, and monitor data from internal and external sources to support business and analytics needs. The position collaborates with business stakeholders, data engineering teams, and privacy compliance partners to implement scalable data solutions, improve data processes, and evaluate emerging technologies that drive innovation and operational efficiency.We are expanding our efforts into complementary data technologies for decision support in areas of ingesting and processing large data sets including data commonly referred to as semi-structured or unstructured data.  Our interests are in enabling data science and search-based applications on large and low latent data sets in both a batch and streaming context for processing.

In this role you will:

• Work with internal business partners to identify, capture, collect, and format data from the external sources, internal systems and the data warehouse to extract features of interest
• Contribute to the evaluation, research, experimentation efforts with batch and streaming data engineering technologies in a lab to keep pace with industry innovation
• Work with data engineering related groups to inform on and showcase capabilities of emerging technologies and to enable the adoption of these new technologies and associated techniques
• Coordinate with Privacy Compliance to ensure proper data collection and handling
• Create and implement business rules and functional enhancements for data schemas and processes
• Coordinate with Privacy Compliance to ensure proper data collection and handling
• Perform data load monitoring and resolution
• Work with internal business clients to problem solve data availability and activation issues