Senior Data Engineer
Core
Design, build, and operate data products transforming connected-vehicle signals into trusted insights, health information, and proactive customer experiences.
Role type
Senior hands-on IC data engineer (vehicle telemetry & AI)
Builds
Production-grade batch and real-time data pipelines, streaming applications, and data products for connected vehicles
Domain
Automotive / Connected Vehicles / Cloud Data Platforms
Deliverable
production ML models | product features | infrastructure
Required skills
Java, Python, SQL, Apache Flink, Apache Spark, Kafka, Azure Kubernetes Service, Azure Event Hubs, Databricks, GraphQL, REST, gRPC, Terraform, Kubernetes, Helm, Argo CD, OpenTelemetry, Datadog, Grafana, Prometheus, Large Language Models, Vector Search, Retrieval-Augmented Generation
Preferred skills
Agentic systems, MLflow, Feature stores, Azure OpenAI Service, pandas, NumPy, scikit-learn, PyTorch, GitHub Actions, Azure DevOps, Time-series data, Geospatial data, Predictive maintenance
Technologies
Apache Flink, Apache Spark, Kafka, Azure Event Hubs, Azure Kubernetes Service, Azure Data Explorer, Azure Databricks, GraphQL, REST, gRPC, Terraform, Helm, Argo CD, OpenTelemetry, Datadog, Grafana, Prometheus, Azure OpenAI Service
Responsibilities
Design and develop production-grade batch and real-time data pipelines for connected-vehicle telemetry; 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 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 data engineering problems such as 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 for high-volume data and event-driven systems; 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 to vehicle and location data; 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 a culture of quality, ownership, and continuous improvement.
Seniority
Senior, hands-on IC with mentorship responsibilities
