Senior Data Engineer

General Motors - Warren, MI

Full-time - Mid Level

Warren, MI

Transportation Equipment Manufacturing

About the position

The Data Engineer role at General Motors is pivotal in designing, developing, and maintaining data pipelines, databases, and data infrastructure that facilitate efficient data collection, storage, and analysis. This position requires close collaboration with data scientists, data infrastructure architects, and data consumption stakeholders to ensure the availability of high-quality data that supports insights and decision-making. The successful candidate will contribute to GM's strategic vision for the future, addressing prioritized business needs through innovative solutions and technical fidelity. The role emphasizes the importance of working effectively across a cross-functional data and stakeholder ecosystem. As a Data Engineer, you will be responsible for building industrialized data assets and optimizing data pipelines to support Business Intelligence and Advanced Analytic objectives. You will collaborate with forward-thinking Data Scientists, BI Developers, System Architects, and Data Architects to deliver value aligned with GM's vision for the future. The role is categorized as hybrid, requiring the successful candidate to report to the Warren, Austin, or Roswell locations at least three times per week. This position does not offer relocation benefits, and any associated costs will be the responsibility of the selected candidate. In this role, you will design, construct, install, and maintain data architectures, including databases and large-scale processing systems. You will develop and maintain ETL (Extract, Transform, Load) processes to collect, cleanse, and transform data from various sources, including cloud environments. Additionally, you will implement security measures to protect sensitive data and ensure compliance with data privacy regulations. Your responsibilities will also include building data solutions that ensure data quality, integrity, and security through validation, monitoring, and adherence to data governance policies. You will administer and optimize databases for performance and scalability, maintain Master Data, Metadata, Data Management Repositories, Logical Data Models, and Data Standards, and troubleshoot data-related issues affecting data quality fidelity. Documentation of data architectures, processes, and best practices for knowledge sharing across the GM data engineering community will also be part of your duties.

Responsibilities

• Design, construct, install and maintain data architectures, including database and large-scale processing systems.
• Develop and maintain ETL (Extract, Transform, Load) processes to collect, cleanse and transform data from various sources inclusive of cloud.
• Design and implement data pipelines to collect, process and transfer data from various sources to storage systems (data warehouses, data lakes, etc.).
• Implement security measures to protect sensitive data and ensure compliance with data privacy regulations.
• Build data solutions that ensure data quality, integrity and security through data validation, monitoring, and compliance with data governance policies.
• Administer and optimize databases for performance and scalability.
• Maintain Master Data, Metadata, Data Management Repositories, Logical Data Models, and Data Standards.
• Troubleshoot and resolve data-related issues affecting data quality fidelity.
• Document data architectures, processes and best practices for knowledge sharing across the GM data engineering community.

Requirements

• 5 to 7+ years of relevant experience.
• Strong skills in SQL, Python, Unix and ability to write efficient ETL on Kubernetes and Cloud platforms.
• Strong understanding and ability to provide mentorship in the areas of data ETL processes and tools for designing and managing data pipelines.
• Experience with big data frameworks and tools like Apache Hadoop, Apache Spark, or Apache Kafka for processing and analyzing large datasets.
• Hands on experience with data serialization formats like JSON, Parquet and XML.
• Consistently designs solutions and build data solutions that are highly automated, performant, with quality checks that provide data consistency and accuracy outcomes.
• Experience in actively managing large-scale data engineering projects, including planning, resource allocation, risk management, and ensuring successful project delivery and adjust style for all delivery methods (ie: Waterfall, Agile, POD, etc.).
• Understands data governance principles, data privacy regulations, and experience implementing security measures to protect data.
• Ability to work effectively in cross-functional teams, collaborate with data scientists, analysts, and stakeholders to deliver data solutions.
• Influential communication skills to effectively convey technical concepts to non-technical stakeholders and document data engineering processes.
• Models a mindset of continuous learning, staying updated with the latest advancements in data engineering technologies, and a drive for innovation.

Benefits

• Paid time off including vacation days, holidays, and parental leave for mothers, fathers and adoptive parents.
• Healthcare (including a triple tax advantaged health savings account and wellness incentive), dental, vision and life insurance plans to cover you and your family.
• Company and matching contributions to 401K savings plan to help you save for retirement.
• Global recognition program for peers and leaders to recognize and be recognized for results and behaviors that reflect our company values.
• Tuition assistance and student loan refinancing.
• Discount on GM vehicles for you, your family and friends.