12 Aug
|
Mercedes-Benz Group
|
Bengaluru
12 Aug
Mercedes-Benz Group
Bengaluru
Tätigkeitsbereich:Forschung & Entwicklung incl. Design
- Fachabteilung:Cloud, Data & Connected Services
- Gesellschaft:Mercedes-Benz Research and Development India Private Limited
- Standort:Mercedes-Benz Research and Development India Private Limited, Bangalore
- Startdatum:sofort
- Veröffentlichungsdatum:18.02.2026
- Stellennummer:MER0003PMN
- Arbeitszeit:Vollzeit
- AufgabenData Infrastructure & Operations
Offer versatile and secure data ingestion, streaming, transformation, analytics and data lake storage paired with self-service compute & ML workspaces so that In-house data teams can spin-up services and create pipelines as per their business requirements
Job description
- Looking for 4-6 years of hand-ons experience with production-level development and operations on AWS or Azure Cloud
- Develop and maintain infrastructure-as-code using Terraform to deploy and manage Kubernetes clusters (AKS) and Databricks environments
- Hands-on experience with data pipeline orchestration tools like Azure Data Factory, Amazon data Pipeline, Apache Spark, Databricks
- Hands-on experience with one or more of stream & batch processing systems: Kafka (Confluent cloud, open source), Apache Storm, Spark-Streaming, Apache Flink, Kappa architecture
- Experience in architecting right storage strategy for use-cases, keeping data processing, data accessibility, data availability and cloud cost considerations
- Proficiency in Data transformation using Kstreams App/KSQL/Processor Libraries
- Data ingestion and data distribution integration experience using managed connectors such as Event Hubs, kafka topics, ADLS2, REST APIs
- Proficiency to set-up & manage open-source stack, including Airflow, Druid, Kafka (open source) OpenSearch, and Superset
- Proficiency in Python scripting for automation and integration tasks
- Utilize FastAPI for building and deploying high-performance APIs
- Handling requirements of managed services, IAM, auto-scaling, High availability, elasticity, networking op
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