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

Responsibilities

Aboute the role:

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.To that end, this role will engage with team counterparts in exploring and deploying technologies for creating data sets using a combination of batch and streaming transformation processes. These data sets may support both off-line and in-line machine learning training and model execution. Other data sets support search engine based analytics. Responsibility also includes coding, testing, and documentation of new or modified scalable analytic data systems including automation for deployment and monitoring. This role participates along with team counterparts to architect an end-to-end framework developed on a group of core data technologies. Other aspects of the role include developing standards and processes for data engineering projects and initiatives.

JOB DUTIES

• Code, test, deploy, monitor, document, and troubleshoot data engineering processing and associated automation in accordance with best practices and security standards throughout the development lifecycle
• Coach junior Data Engineers and review code and output for timeliness, accuracy and completeness
• Work closely with data scientists, data architects, ETL developers, other IT counterparts, and business partners to identify, capture, collect, and format data from the external sources, internal systems and the data warehouse/data lake to extract features of interest
• Significantly contribute to the evaluation, research, experimentation efforts with batch and streaming data engineering technologies to keep pace with industry innovation while assessing business impact and viability for use cases associated with efforts in hand
• Work with data engineering related groups to inform on and showcase capabilities and to enable the adoption of new technologies and associated techniques
• Significantly contribute to the definition and refinement of processes and procedures for the data engineering practice
• Educate and develop ETL developers and Data Engineers on data engineering cloud-based initiatives
• Perform other duties as assigned
• Conform with all company policies and procedures

Qualifications

What makes you a dream candidate?

• Proficient with processing large data sets using Hadoop, HDFS, Spark,Kafka, Flume, Hbase, Solr or similar distributed systems. Experience in ingesting real-time and batch Telematics data to handle high volume/big data piepeline is highly desirable
• Proven track record with ingesting various source data formats such as JSON, Parquet, SequenceFile Cloud Databases, event-based systems, Relational Databases such as Oracle
• Extensive experience with Cloud technologies (such as Azure, AWS, GCP) and native toolsets such as Azure ARM Templates, Hashicorp Terraform
• Experience in ingesting Guidewire data and its various data models (e.g. Could Data Access, Data Hub) is highly desirable
• Deep understanding of cloud computing technologies, business drivers and emerging computing trends
• 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
• Experience with Azure cloud services to include but not limited to Data Lake Storage Gen2, Synapse Analytics, Data Factory, Databricks, Delta Lake
• Working knowledge of Object Storage technologies to include but not limited to S3, Minio, Ceph, ADLS etc
• Experience with containerization to include but not limited to Docker, Kubernetes, AKS, Spark on Kubernetes, Spark Operator
• Working knowledge of Agile development, Scrum or Kanban, SAFe
• Strong 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)
• Proven track record with NoSQL data stores such as CosmosDB, MongoDB, Cassandra, Redis, Riak or other technologies that embed NoSQL with search such as MarkLogic or Lily Enterprise
• In-depth knowledge of ETL/ELT concepts and low-code technologies such as Informatica, DataStage, Ab Initio

Skills

• Ability to quickly prototype and perform critical analysis and use creative approaches for solving complex problems
• Excellent interpersonal, written, and verbal communication skills
• Excellent analytical and troubleshooting skills
• Ability to coach, develop and lead others
• Ability to accept change and to adapt to shifting organizational challenges and priorities
• Advanced ability to analyze problems, correlate data from multiple sources and communicate pertinent information to the appropriate support teams
• Ability to manage multiple tasks simultaneously while maintaining composure under pressure
• Ability to evaluate problems and issues quickly and make recommendations for courses of action
• Ability to make independent decisions and use sound judgment in relation to the potential management of team members
• Ability to prioritize tasks and ensure their completion in a timely manner

Additional Knowledge Skills and Abilities

• Working knowledge of Databricks with Delta Lake, preferably on Azure

Education

• Bachelor’s Degree in related field or equivalent work experience required

Experience

• 5-7 years software engineering to include Spark with Java, Scala, or Python Python/PySpark preferred required
• 5-7 years hands-on experience with ETL/ELT pipelines to process Big Data in Data Lake Ecosystems on-prem and/or in the cloud required
• 5-7 years hands-on experience with SQL, data modeling, and relational databases such as Oracle, DB2 and Postgres required
• Experience in auto insurance industry highly desirable
• 2-3 years Databricks on Azure preferred

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.

Work Life Balance: 100% Remote

#LI-SC1

#LI-Hybrid

Salary

The base salary range for this role is: USD $112,200.00 to $213,100.00.

At GM Financial, we strive for transparency in all aspects of our business, including pay equity. This is the GM Financial pay range for this role and job level. The exact salary and compensation will vary based on factors like knowledge, skills, experience, and education.

This role is eligible to participate in a performance-based incentive plan. Full time employees are eligible to participate in health benefits on day one of employment.

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GM Financial is an Equal Opportunity Employer and is committed to diversity and inclusion at every level of our organization. We do not discriminate against any applicant or employee based on race, color, age, gender, national origin, religion, sexual orientation, gender identity, veteran status, disability or any other federal, state or local protected class.

GM Financial has an accommodation process in place and provides accommodations for applicants and employees with disabilities. If you require a reasonable accommodation because of a disability, please contact Human Resources at 1-866-411-4748 or by e-mail at HRConnection@gmfinancial.com.