Staff Software Engineer, Data Platform Services and API Development

General Motors•Austin, TX

21h•Hybrid

About The Position

The Role Software-defined vehicles represent a new paradigm for automakers and consumers, fueled by technological advancements and an escalating demand for intelligent transportation solutions. At General Motors, we have embarked on an ambitious journey to pioneer next-generation data platforms to support all our business units. To fulfill this mission, Operational Data Platforms organization is seeking an experienced, hands-on Full Stack Java Development Lead with strong expertise in designing and building cloud-native microservices and APIs. This role is an individual contributor position focused primarily on backend engineering—Java services, distributed systems, API design, and data persistence (SQL and NoSQL). While full-stack experience is expected, the emphasis is on backend/API development rather than interactive front-end frameworks. As a staff engineer, you will be at the forefront of creating and implementing scalable and reliable platform services that enable rapid deployment of applications largely in a domain agnostic fashion. We will be relying on these services to help shrink our time to market and adopt faster releases for continuous improvement.

Requirements

Minimum of 8 years of hands-on software development experience, with demonstrated expertise in:
Java 11+, Spring Boot, and Spring Cloud
RESTful API design and implementation
Microservices architectures and distributed systems
Object-oriented design principles and Java design patterns
Strong experience building cloud-native applications on Azure, AWS, or GCP
Hands-on experience with containerization and orchestration technologies, including Docker and Kubernetes
Proven experience with CI/CD pipelines (e.g., Jenkins, GitHub Actions, GitLab CI)
Proficiency with SQL databases (PostgreSQL, MySQL, Oracle) and NoSQL data stores (MongoDB, CosmosDB, Cassandra)
Solid understanding of application and API security best practices, including OAuth2, JWT, mTLS, and API gateways
Ability to operate as a technical lead and decision-maker while remaining a strong individual contributor
Strong analytical, debugging, and problem-solving skills
Excellent communication and documentation capabilities
Ability to collaborate effectively in an agile, fast-paced environment
BS/MS/PhD in Computer Science or Engineering preferred

Nice To Haves

Knowledge of networking concepts, including routing tables, firewall rules, load balancing, and network security.
Hands-on experience with service observability: Prometheus, Grafana, ELK/EFK, Datadog, OpenTelemetry.
Exposure to challenges of building scalable applications for device and sensor data capture & consumption

Responsibilities

Lead technical design discussions and create detailed architecture for new features and services.
Guide junior engineers through code reviews and technical mentorship (without direct people management).
Drive high engineering standards: unit testing, integration testing, code quality, automated testing frameworks.
Ensure secure coding practices, API hardening, and adherence to enterprise security policies.
Work closely with product owners, architects, and platform teams to translate requirements into technical solutions.
Provide backlog input, effort estimates, and help shape technical roadmaps.
Design, develop, and maintain scalable Java-based cloud microservices (Spring Boot & Spring Cloud).
Develop services for cloud environments (Azure, AWS or GCP) including containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
Build robust, secure, and versioned RESTful APIs and integrations.
Implement asynchronous messaging, event-driven patterns, and distributed processing.
Ensure reliability, observability, and monitoring through logging, tracing, and metrics.
Design and optimize data models leveraging RDBMS (PostgreSQL, MySQL, Oracle, etc.) and NoSQL databases (MongoDB, CosmosDB, Cassandra).
Implement efficient data access layers and query strategies for performance and scalability.
Diagnose performance bottlenecks and optimize services for throughput and latency.