Data Engineer II

Overview

Why GMF Technology?

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.

Responsibilities

We seek a Data Engineer who brings a robust skill set and extensive experience in cloud-based data engineering experience particularly within the realm of Azure and Databricks using Python, PySpark and cloud SQL. Critical thinking and problem-solving abilities are paramount, as you will navigate evolving and complex requirements and collaborate with stakeholders across diverse technical backgrounds. Your primary focus will revolve around data engineering development tasks, serving as a visionary alongside Data Engineering leads to refine and expand reusable libraries and common framework, ensuring it can accommodate the growing volume of incoming projects. You will also engage into engineering tasks, such as constructing pipelines and deployments that bolster various programs, projects, and initiatives supporting multiple customer needs. 

What makes you an ideal candidate?

• Work closely with data scientists, data architects, developers, other IT counterparts, and business partners to identify, capture, collect and format data from the external sources, internal systems, and the data warehouse to extract features of interest.
• Designing and implementing internal process improvements including pipeline redesigns for greater scalability, optimizing data delivery, and automating manual processes.
• Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure and Databricks technologies
• Experience with ingesting various source data formats such as JSON, Parquet, SequenceFile, Cloud Databases, MQ, No SQL, flat files, Event Hubs and Relational Databases such as Oracle
• Experience with Cloud technologies (such as Azure, AWS, GCP) and native toolsets such as Azure ARM Templates, Hashicorp Terraform, AWS Cloud Formation
• Thorough understanding of Hybrid Cloud Computing: virtualization technologies, Infrastructure as a Service, Platform as a Service and Software as a Service Cloud delivery models and the current competitive landscape
• Working knowledge of Object Storage technologies to include but not limited to Data Lake Storage Gen2, Delta Lake, S3, Minio, Ceph, ADLS
• Working knowledge of NoSQL data stores such as CosmosDB, MongoDB, Cassandra, Redis, Riak or other technologies that embed NoSQL with search such as MarkLogic or Lily Enterprise
• Working knowledge with containerization to include but not limited to Dockers, Kubernetes, Spark on Kubernetes, Spark Operator
• Proficient in SQL and Python, with the ability to utilize these tools effectively
• Seasoned in refining and enhancing existing data pipelines to unlock peak efficiency and exceptional performance
• Self-motivated problem solver with a keen eye for identifying and rectifying data inaccuracies
• Collaborative mindset, thriving in cross-functional teams by effectively sharing knowledge and contributing to the delivery of high-quality products
• Collaborate with the team to identify opportunities for innovation and improvement, actively contributing to the continuous evolution of our data infrastructure and engineering capabilities
• Working knowledge of Agile development /SAFe, Scrum and Agile Software Development methodologies
• Ability to thrive in an Agile/Scrum team environment
• Background with source control management systems (GIT or Subversion); Build Systems (Maven, Gradle, Webpack); Code Quality (Sonar); Artifact Repository Managers (Artifactory), Continuous Integration/ Continuous Deployment (Azure DevOps)
• SQL experience: querying data and sharing what insights can be derived
• Understanding of cloud solutions such as Google Cloud Platform, Microsoft Azure & Amazon AWS cloud architecture & services
• Knowledgeable of best practices in information technology governance, privacy, compliance and security topics

Qualifications

Experience

• Bachelor’s Degree in related field or equivalent work experience required
• 4-6 years of hands-on experience with data engineering required
• 3-5 years of hands-on experience with processing large data sets required
• 3-5 years of hands-on experience with SQL, data modeling, relational databases and/or no SQL databases 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: Flexible hybrid work environment, 2-days a week in office

Note:Please note we are not able to consider candidates who require visa sponsorship for this position.

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