Senior Data Engineer: Real-Time IoT, Databricks & Azure

General Motors Company; Austin (TX); Hybrid; USD 125,000 - 169,000; Full time

Benefits offered by this job

Health benefits

GM vehicle discounts

Relocation benefits

Job summary

General Motors Energy Data Engineering is seeking a Senior Software Engineer to design, build, and operate scalable cloud data solutions in Azure. Hybrid role in Austin, TX with three days onsite weekly.

You will implement real-time pipelines using Flink, Pulsar, and Kafka, and develop GraphQL APIs over PostgreSQL. You will mentor engineers, contribute to architecture decisions, and champion best practices, testing, observability, and secure development while leveraging Databricks and

Qualifications

• 7+ years of professional software development experience.
• Strong proficiency in Java and object-oriented design.
• Experience building production-grade backend services and distributed systems.
• Hands-on experience with one or more streaming technologies, preferably Apache Flink, Apache Pulsar, and Apache Kafka.
• Strong understanding of event-driven architecture, messaging patterns, data partitioning, consumer groups, delivery semantics, and stream processing.
• Experience designing and developing GraphQL APIs.
• Strong experience with PostgreSQL, including schema design, SQL, performance tuning, indexing, and transaction management.
• Experience with Databricks and data engineering or analytics platforms.
• Experience developing and deploying applications in Microsoft Azure.
• Practical CI/CD experience with automated testing, packaging, deployment, and release management.
• Experience with source control and collaborative development workflows, such as Git and pull requests.
• Strong troubleshooting, communication, and technical documentation skills.

Responsibilities

• Design, develop, test, and maintain scalable Java services and distributed applications.
• Build and optimize real-time data streaming pipelines using Apache Flink, Apache Pulsar, and Apache Kafka.
• Develop reliable event-driven services with strong attention to throughput, latency, resiliency, ordering, replay, and fault tolerance.
• Design and implement an Operational Data Store (ODS) layer using GraphQL and PostgreSQL.
• Develop GraphQL APIs and services that provide secure, efficient, and well-structured access to operational data.
• Design relational schemas, queries, indexes, and data-access patterns for PostgreSQL.
• Integrate streaming and operational data services with Databricks and cloud-based data platforms.
• Deploy and operate applications in Microsoft Azure using cloud-native architecture and services.
• Implement automated build, test, deployment, and release processes through CI/CD pipelines.
• Apply software engineering best practices, including code reviews, automated testing, observability, documentation, and secure development.
• Troubleshoot complex issues across application, streaming, database, and cloud environments.
• Participate in technical design discussions and contribute to architecture decisions.
• Mentor other engineers and help establish engineering standards and reusable patterns.
• Use generative AI tools and effective prompting techniques to accelerate development, troubleshoot issues, create documentation, and improve engineering productivity while applying appropriate security and data-handling practices.

Skills

Java

Distributed systems

Streaming technologies

GraphQL

PostgreSQL

Databricks

Microsoft Azure

CI/CD

Git

Tools

Apache Flink

Apache Pulsar

Apache Kafka

Databricks

GraphQL APIs

PostgreSQL

Azure cloud services

Job description

General Motors Energy Data Engineering is seeking a Senior Software Engineer to design, build, and operate scalable cloud data solutions in Azure. Hybrid role in Austin, TX with three days onsite weekly.

You will implement real-time pipelines using Flink, Pulsar, and Kafka, and develop GraphQL APIs over PostgreSQL. You will mentor engineers, contribute to architecture decisions, and champion best practices, testing, observability, and secure development while leveraging Databricks and