Senior Data Engineer

Key Skills

Apache Kafka, Data Architecture, Data Engineering, Data pipelines, Data science techniques, Effective communication skills, ETL frameworks, Metadata, Python Programming, SPARK Programming, SQL, Unix Operating system, XML-JSON

Job Description

As a Data Engineer, you will build industrialized data assets and optimize data pipelines in support of Business Intelligence and Advance Analytic objectives. You will work closely with our forward-thinking Data Scientists, BI Developers, System Architects and Data Architects to deliver value to our vision for the future. Are you ready to join a future facing team?

What You'll Do

• 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

Your Skills & Abilities (Required Qualifications)

• 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

This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, Austin, or Roswell three times per week, at minimum.

This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.

Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.