Senior Data Engineer

General Motors

. Design and develop production-grade batch and real-time data pipelines for connected-vehicle telemetry, trip and session data, diagnostic signals, and vehicle-health indicators .

Posted 9/24/2026full-timeAustin • Texas • United StatesSenior💰 $125,000 - $191,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing production-grade data pipelines and applications using technologies such as Apache Flink, Apache Spark, and Microsoft Azure. Proficient in applying machine learning and artificial intelligence techniques to enhance data quality and operational efficiency.

Highest-signal resume keywords

Data Pipeline DevelopmentApache FlinkMicrosoft AzureMachine Learning ApplicationAPI Design

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Hard Skills

JavaPythonSQLObject-Oriented DesignData StructuresAlgorithmsAutomated TestingData ModelingPerformance OptimizationSchema Evolution

Soft Skills

CollaborationCommunicationMentoringProblem-SolvingTechnical Documentation

Tools & Technologies

Azure Kubernetes ServiceAzure DatabricksKafkaOpenTelemetryDatadogGrafanaPrometheusTerraformHelmArgo CD

Industry Keywords

Data EngineeringDistributed SystemsEvent-Driven SystemsPrivacy-Aware Data HandlingGenerative Artificial Intelligence

Tech Stack

Tools & technologies

ApacheAzureCloudDistributed SystemsGrafanaGraphQLGRPCJavaKafkaKubernetesPrometheusPythonSparkSQLTerraformVault

About the role

Key responsibilities & impact

Design and develop production-grade batch and real-time data pipelines for connected-vehicle telemetry, trip and session data, diagnostic signals, and vehicle-health indicators
Build streaming applications that ingest, enrich, validate, deduplicate, curate, and publish event-driven data
Develop reliable data products using Apache Flink, Apache Spark Structured Streaming, Java, Python, and SQL
Work with Microsoft Azure services including Azure Kubernetes Service, Event Hubs, Azure Data Explorer, Azure Key Vault, Azure Databricks, Azure Monitor, and Application Insights
Design and maintain data contracts, schemas, APIs, and event models using GraphQL, REST, gRPC, JSON, and cloud-event patterns
Apply artificial intelligence and machine learning to anomaly detection, data-quality triage, predictive health signals, intelligent operations, and engineering productivity
Build or integrate generative artificial intelligence capabilities, including large language model applications, embeddings, vector search, retrieval-augmented generation, agentic workflows, prompt engineering, evaluation, and safety guardrails
Create automated tests, performance benchmarks, integration tests, and validation checks
Establish observability with OpenTelemetry, Datadog, Grafana, Prometheus, dashboards, monitors, service-level objectives, and actionable alerts
Secure data in transit and at rest and apply privacy, consent, retention, lineage, access-control, and regional compliance requirements
Automate infrastructure and delivery using Kubernetes, Helm, Argo CD, Terraform, continuous integration, continuous delivery, and infrastructure-as-code practices
Participate in architecture reviews, code reviews, incident response, root-cause analysis, operational readiness, and on-call support as needed
Mentor engineers, raise technical standards, document design decisions, and contribute to continuous improvement

Requirements

What you’ll need

Bachelor’s degree in computer science, computer engineering, data engineering, information systems, or a related technical field, or equivalent experience
5+ years of professional experience in data engineering, software engineering, distributed systems, or a related field
Strong hands-on experience with Java or Python, SQL, object-oriented design, data structures, algorithms, and automated testing
Experience designing and operating production data pipelines using Apache Flink, Apache Spark, Kafka, Azure Event Hubs, or comparable streaming technologies
Experience with cloud-native development on Microsoft Azure and containerized workloads running on Kubernetes
Experience with Databricks, Delta Lake, distributed data processing, data modeling, and performance optimization
Experience designing APIs and event-driven systems using GraphQL, REST, gRPC, asynchronous HTTP clients, or equivalent technologies
Experience with schema evolution, data contracts, data-quality validation, lineage, observability, and privacy-aware data handling
Demonstrated experience applying machine learning, artificial intelligence, or generative artificial intelligence in a production engineering, analytics, or data-product environment
Working knowledge of large language models, embeddings, vector databases or vector search, retrieval-augmented generation, prompt design, model evaluation, and responsible artificial intelligence practices
Ability to troubleshoot complex distributed systems and communicate technical decisions clearly to both technical and nontechnical audiences
Ability to work effectively in a collaborative, agile, cross-functional environment
GM does not provide immigration-related sponsorship; applicants must not require GM immigration sponsorship now or in the future

Benefits

Comp & perks

Relocation benefits may be available
Medical insurance
Dental insurance
Vision insurance
Health Savings Account
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
Incentive pay program with payouts based on company, job-level, and individual performance