Job description

Why GM Financial?

If you have a vision of data and analytics as a service to support strategic initiatives using the latest tools, languages, and platforms in the cloud – we have the role, career, and challenge that you are looking for. Are you a builder, engineer, do you have a passion for data ops, MLOps and DevOps, are you a governance/metadata champion – look no further than GM Financial. In 2021, the Global Data and Analytics team received executive sponsorship and funding to build an enterprise cloud data and analytics platform. Our Mission is to partner with the business and technical teams to enable all users with data and analytics solutions. If you envision a world where innovative digital and cloud data platforms are built to transform customer contact, interaction and value through increased experimentation and insight generation, then GM Financial is the place for you.

At GM Financial, we’re looking for an experienced and highly motivated Data Engineer. The Data Engineer will help lead data transformation at GM Financial to support data science, analytics, and business teams globally. This role will be responsible for system API integration, data operations, engineering, pipeline development, and orchestration from ingestion through consumption zones. In this Agile environment, the Data Engineer will partner with stakeholders to influence strategic decisions, and execution of data products. This role will ensure that all data products are available in the cloud to both business, and technical requirements.

Why Work Here?
  • A work environment built on teamwork, flexibility, and respect.
  • Flexible work options based on business needs.
  • GM Financial is committed to strengthening the communities where we live and work. Each year, through our Signature Events program, each year we select several philanthropic organizations to support.
  • Professional growth and development programs to help advance your career, as well as tuition reimbursement.
  • GM Financial 401(k) Savings Plan featuring a company’s match.
  • Paid holidays and paid time off and floating holiday’s
  • All full-time team members receive eight hours of paid time off to volunteer each quarter
What you will do:
  • Provide technical expertise to support ingestion and migration of internal and external data in multiple formats and types to the cloud.
  • Deploy developed data solutions, user applications, databases and other data solutions and capabilities.
  • Design and develop specialized data solutions, applications and databases using an Agile approach within a DevOps/DataOps environment.
  • Collaborate with cloud data engineering, MLOps, and Data Science teams to design and launch data feature stores.
  • Develop relationships with key customer business and technical decision makers: drive long-term cloud data adoption, enable cloud data advocacy.
  • Collaborate with Data Leadership to define cloud data solutions to support Data & Analytics priorities and goals.
  • Share insights and best practices and connect with teams to remove key blockers with leadership and cloud data engineering team.
  • Collaborate on the flow of data from transactional systems, data management, external vendors, and master data layer, to the cloud data and analytics platform with business definitions, metadata, requirements, and transformations in the data domain.

What you bring to the table:
  • 1 + years of experience in designing, engineering, and implementing cloud data solutions, collaborating with the business to build enterprise scale data solutions to support machine learning, artificial intelligence and analytics.
  • 1 + years of cloud data development solutions, PaaS, SaaS, IaaS, Serverless, Data Orchestration, API Management, microservice frameworks, container orchestration.
  • 2 + years of experience in data engineering, data operations, IT, analytics teams or equivalent.
  • Bachelor’s degree in the field of Computer Science/Engineering, Analytics, Data Science, Mathematics or related discipline. Master’s degree is a plus.

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