Senior Data Engineer

GM•Austin, TX

1d•Hybrid

About The Position

The Senior Data Engineer designs and operates reliable data platforms while helping build user-facing applications that make data accessible and actionable. The role combines data engineering with hands-on React front-end development. The engineer partners with product, analytics, and engineering teams to deliver end-to-end solutions, from data ingestion and transformation through APIs and user interfaces. The position is hybrid, with the successful candidate expected to report to the Austin Technical Center at least three times per week, or more often if business needs require it. The role may be eligible for relocation benefits. The expected base compensation is $125,000–$168,650, with potential incentive pay based on company performance, job level, and individual performance. GM does not provide immigration-related sponsorship for this role.

Requirements

At least 5 years of professional experience in data engineering, software engineering, or a closely related field.
Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent experience.
Strong proficiency in SQL and a data-engineering programming language such as Python, Scala, or Java, and cloud data platforms such as Azure, AWS, or GCP.
Experience designing production-grade ETL/ELT pipelines and working with data warehouses, data lakes, or lakehouse platforms.
Hands-on experience building or maintaining front-end applications with React; familiarity with TypeScript and component-based UI patterns.
Experience integrating front-end applications with REST or GraphQL APIs and handling asynchronous data states, errors, and loading behavior.
Understanding of data modeling, schema evolution, data quality, and distributed processing concepts.
Experience with cloud platforms and modern deployment or orchestration tools.
Strong communication and problem-solving skills, with the ability to work across technical and nontechnical teams.

Nice To Haves

Experience with Apache Spark, Kafka, Airflow, dbt, or comparable technologies.
Experience with Snowflake, BigQuery, Databricks, Redshift, or comparable cloud data platforms.
Familiarity with Docker, Kubernetes, infrastructure as code, and cloud-native architectures.
Experience with front-end testing tools, accessibility practices, and design systems.
Experience implementing authentication, authorization, and secure handling of sensitive data.
A track record of mentoring teammates and leading delivery across multiple systems or teams.

Responsibilities

Design, build, and maintain scalable batch and streaming data pipelines.
Develop and optimize data models, warehouses, and lakehouse solutions for analytics and application use cases.
Build and maintain data services and APIs that securely expose trusted, well-documented data to applications.
Develop responsive front-end features using React, JavaScript or TypeScript, and modern web development practices.
Collaborate with product designers and stakeholders to translate workflows and data needs into clear, usable interfaces.
Establish data quality checks, observability, lineage, and alerting; investigate and resolve pipeline and application issues.
Improve performance, reliability, security, and cost efficiency across data and application systems.
Apply engineering best practices, including code review, automated testing, CI/CD, documentation, and maintainable architecture.
Mentor engineers, provide technical guidance, and contribute to roadmaps and architectural decisions.

Benefits

Medical, dental, and vision benefits.
Health Savings Account and Flexible Spending Accounts.
Retirement savings plan.
Sickness and accident benefits.
Life insurance.
Paid vacation and holidays.
Tuition assistance programs.
Employee assistance program.
GM vehicle discounts.
Potential incentive pay based on company performance, job level, and individual performance.
Possible relocation benefits.