General Motors - Washington, DC

posted 2 months ago

Full-time - Senior
Remote - Washington, DC
Transportation Equipment Manufacturing

About the position

The Marketing Applied Sciences team at General Motors is dedicated to developing analytics-driven solutions that empower GM organizations to achieve their business objectives. As a Senior Data Engineer, you will be an integral part of a multi-disciplinary team, collaborating with various experience levels to design, develop, and deploy analytic models that support business-facing analytic groups. This role emphasizes both advanced analytics strategy and applied, project-based solutions, focusing on the company's most critical business areas. In this position, you will be responsible for building analytical data sets that support Advanced Analytics projects. You will work closely with innovative Researchers and Data Scientists to deliver value aligned with GM's vision for the future. Your contributions will help shape the data products that drive analytics solutions, ensuring compliance with data privacy and security policies to protect sensitive customer data. You will also play a key role in promoting cloud-first technologies and industry-standard Data Engineering practices, collaborating with cross-functional teams including data governance, data architecture, release management, Data Ops & ML Ops, and infrastructure. Your responsibilities will include automating new and existing data processes, particularly those involving non-structured sources, to eliminate manual efforts in data gathering and ingestion. Staying abreast of emerging trends and technologies in Data Engineering will be crucial, as you will proactively seek opportunities for improvement and innovation within the organization. Additionally, fostering a culture of continuous learning and knowledge sharing within the team and the broader data engineering community will be a key aspect of your role.

Responsibilities

  • Collaborate with the MAS team functions to develop data products for analytics solutions.
  • Design and develop data products that comply with data privacy and security policies to protect sensitive data, including customer data.
  • Drive the adoption of cloud-first technologies and industry-standard Data Engineering practices to enhance engineering capabilities.
  • Collaborate with cross-functional teams including data governance, data architecture, release management, Data Ops & ML Ops, and infrastructure as required.
  • Automate new and existing data processes, particularly for non-structured sources, to eliminate manual data gathering and ingestion efforts.
  • Stay updated with emerging trends and technologies in Data Engineering and identify opportunities for improvement and innovation.
  • Foster a culture of continuous learning, knowledge sharing, and development within the team and the broader data engineering community.

Requirements

  • 5+ years of hands-on experience delivering enterprise-scale data and analytics solutions using modern hybrid cloud technologies, focusing on data curation for Customer Experience data science modeling and reporting.
  • Strong problem-solving and analytical skills with practical experience analyzing and curating large scale customer event data products from disparate data sources.
  • In-depth knowledge of industry-standard Data Engineering practices including data privacy & security, ETL/ELT, data architecture, data quality assurance, performance optimization, source code management, release management, and operations.
  • Expert programming skills in data and analytics platforms, big data processing frameworks and languages, and development tools including Azure (or similar), Databricks, Spark, Python, SQL, and GitHub.
  • Effective communication and people skills, with the ability to collaborate effectively with cross-functional technical teams and non-technical stakeholders.
  • Naturally curious with the ability to work independently and proactively.
  • Experience working in an Agile development environment.

Nice-to-haves

  • Master's degree in Computer Science, Data Science, or a related field.

Benefits

  • Medical, dental, and vision insurance options.
  • Health Savings Account and Flexible Spending Accounts.
  • Retirement savings plan with company and matching contributions.
  • Sickness and accident benefits.
  • Life insurance coverage.
  • Paid vacation and holidays, including parental leave for mothers, fathers, and adoptive parents.
  • Tuition assistance programs and student loan refinancing.
  • Employee assistance program.
  • GM vehicle discounts.
  • Global recognition program for peers and leaders.
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