Daimler Truck Innovation Center India seeks a DTICI Engineering Data Analysis Engineer to lead data-driven innovation. We are looking for a skilled and motivated professional with hands-on experience in Kubernetes, data engineering, and analytics platforms. The ideal candidate will have strong exposure to operating containerized workloads in production, building and maintaining data pipelines, and supporting analytics and AI/ML use cases. This role requires close collaboration with internal and external stakeholders and a strong focus on reliability, observability, and data-driven decision-making.
Responsibilities- Operate and manage Kubernetes clusters in production environments, ensuring high availability, performance, and reliability
- Troubleshoot and analyze pod failures, performance issues, and deployment challenges using kubectl, logs, metrics, and events
- Work with Kubernetes resources such as Pods, Deployments, StatefulSets, and CronJobs
- Build, maintain, and enhance ETL pipelines for large-scale data processing
- Develop and maintain dashboards and monitoring solutions using Grafana (preferred) and/or Power BI
- Monitor Kubernetes clusters using tools like Prometheus and Grafana
- Implement and support centralized logging solutions such as ELK, EFK, or Loki
- Use Python for data analysis, feature engineering, data wrangling, and exploratory data analysis (EDA)
- Contribute to the building, training, and deployment of AI/ML models
- Process and analyze large-scale datasets using Apache Spark and related libraries
- Collaborate with internal teams and external stakeholders to gather requirements and deliver solutions
- Work with ServiceNow or similar ticket management tools to manage incidents, requests, and changes
- Prepare analysis, reports, and presentations using Microsoft Excel and PowerPoint
- Proven experience operating Kubernetes in production
- Strong understanding of container orchestration concepts and Kubernetes architecture
- Hands-on experience with Python for data analysis and development
- Experience with ETL tools and data pipeline development
- Familiarity with Apache Spark and big data processing frameworks
- Knowledge of monitoring and logging tools in cloud-native environments
- Strong communication and stakeholder management skills
- Preferred Experience on Databricks.
Preferred Qualifications
- Experience working with Grafana for visualization and observability
- Hands-on experience with Databricks
- Exposure to AI/ML model lifecycle management
- Basic understanding of the automotive domain and related business use cases
Skills Required
- Proven experience operating Kubernetes in production
- Strong understanding of container orchestration concepts and Kubernetes architecture
- Hands-on experience with Python for data analysis and development
- Experience with ETL tools and data pipeline development
- Familiarity with Apache Spark and big data processing frameworks
- Knowledge of monitoring and logging tools in cloud-native environments (Prometheus, Grafana, ELK/EFK/Loki)
- Experience working with ServiceNow or similar ticket management tools
- Strong communication and stakeholder management skills
- Experience working with Grafana for visualization and observability
- Hands-on experience with Databricks
- Exposure to AI/ML model lifecycle management
- Basic understanding of the automotive domain and related business use cases
- Ability to prepare analysis, reports, and presentations using Microsoft Excel and PowerPoint
What We Do
Daimler Trucks North America, LLC headquartered in Portland, Oregon, is the leading heavy-duty truck manufacturer in North America. Daimler Trucks North America produces and markets commercial vehicles under the Freightliner, Western Star and Thomas Built Buses nameplates. Daimler Trucks North America is a Daimler company, the world's leading commercial vehicle manufacturer.
