Senior Data Engineer

Job Description

This role is based remotely but if you live within a 50-mile radius of [Austin, Detroit, Milford or Mountain View], you are expected to report to that location three times a week, at minimum.

The Role

The Marketing Applied Sciences team is responsible for developing analytics-driven solutions to help GM Marketing Organizations achieve their business goals. The Sr. Data Engineer role is responsible for designing, developing and maintaining data pipelines, databases and data infrastructure to enable the efficient data collection, storage and analysis in support of marketing strategies. This role requires collaboration with data scientists, data infrastructure architects and data consumption stakeholders to ensure the availability of high-quality data for insights and decision making is available and will deliver value to the GM strategic vision for the future and meet prioritized business needs.  This role drives to deliver innovative solutions with technical fidelity and thrives to work effectively across a cross-functional data and stakeholder ecosystem. 

What You’ll Do

• Develop accurate, consistent analytical datasets to support advanced data science and business intelligence initiatives. 
• Evaluate business requirements, identify relevant data sources, and create datasets that enable actionable insights. 
• Profile and assess data quality to ensure alignment with business objectives and analytical needs. 
• Integrate and transform data from multiple sources, building scalable and optimized data pipelines. 
• Maintain comprehensive metadata, logical models, and data dictionaries for all analytical assets. 
• Act as the subject matter expert (SME) for analytical datasets, providing guidance and resolving inquiries from data scientists. 
• Design and implement process improvements, including automation, data delivery optimization, and infrastructure scalability. 
• Collaborate with business and technology partners to address data-related issues and define infrastructure requirements. 
• Ensure data quality, security, and compliance with governance and privacy regulations. 
• Lead and mentor team members and contract resources, driving best practices and educating peers on emerging technologies. 

Your Skills & Abilities (Required Qualifications)

• Bachelor’s degree in Computer Science, MIS, Software Engineering, or a related field.
• 5 - 7+ years of data engineering/development experience, including Python or Scala, SQL, and relational/non-relational data storage. (ETL frameworks, big data processing, NoSQL).
• 3+ years of experience as a data engineer or in a similar role.
• 3+ years of experience in distributed data processing (Spark) and container orchestration (Kubernetes).
• Proficiency in data streaming in Kubernetes and Kafka.
• Experience with cloud platforms – Azure preferred; AWS or GCP also considered. 
• Solid understanding of CI/CD principles and tools.
• Familiar with predictive / analytical modeling techniques, theories, principles, and practices.  
• Strong understanding of performance optimization techniques such as partitioning, clustering, and caching.
• Proficiency with SQL, key-value datastores, and document stores.
• Familiarity with data architecture and modeling concepts to support efficient data consumption.