Key skills
AWSTerraformGrafanaPrometheusPythonBashPowerShellAWS CLICI/CD pipelinesKubernetesData-as-a-ServiceIncident handlingDatabricksSparkKafkaHadoopJenkinsGitHub ActionsEC2S3RDSRoute53IAMSQSKinesisGitHubGitLabCI/CDCommunicationCloud Security
About this role
Mobilisights is a Data-as-a-Service business unit of Stellantis, unlocking real-time insights from millions of connected vehicles worldwide. The role involves monitoring, operating, and improving cloud and data platforms, requiring independence and ownership during NA coverage hours.
Responsibilities:
- Monitor, operate, and support cloud and data platforms during NA coverage hours
- Participate in a 24×7 on-call SRE rotation using a follow-the-sun model
- Troubleshoot and resolve production incidents independently; lead incident response when required
- Monitor availability, latency, and system health using Grafana and Prometheus
- Define and track SLIs and SLOs to improve service reliability
- Drive blameless postmortems and ensure permanent incident remediation
- Build and maintain infrastructure using Terraform and automation scripts
- Act as a hands-on contributor to AWS infrastructure (VPC, EC2, S3, IAM, RDS, ELB, Route53)
- Continuously improve reliability, scalability, security, and cost efficiency
Requirements:
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
- A minimum of 3 years of experience in SRE, DevOps, or Cloud Operations
- Hands-on experience managing AWS-based infrastructure
- Strong experience with Terraform and infrastructure-as-code
- Practical experience with Grafana and Prometheus
- Automation mindset using Python, Bash, PowerShell, or AWS CLI
- Experience participating in on-call rotations and production support
- Working knowledge of CI/CD pipelines (GitHub Actions, GitLab, Jenkins, etc.)
- Understanding of cloud security best practices and incident response
- Highly self-motivated and proactive; comfortable working independently
- Strong sense of ownership and accountability
- Clear and effective communication skills
- Calm, structured approach to incident handling
- Able to collaborate effectively across global teams and time zones
- Experience supporting data platforms or Data-as-a-Service (DaaS) products
- Exposure to streaming and event-driven systems (Kafka, Kinesis, SQS, etc.)
- Experience working with high-volume, real-time telemetry or IoT data
- Familiarity with data pipelines (batch and streaming) and data reliability concepts
- Experience with big data technologies (Spark, Flink, Hadoop, Iceberg, Delta Lake, Databricks, etc.)
- Basic understanding of data quality, data latency, and data availability SLIs/SLOs
- Experience operating Kubernetes or containerized workloads in cloud environments
- Understanding of cost optimization for large-scale data ingestion and storage in AWS
- Prior experience in automotive, mobility, IoT, or connected devices ecosystems