T10 to T9 Conversion

Tätigkeitsbereich:Forschung & Entwicklung incl. DesignFachabteilung:Cloud, Data & Connected ServicesGesellschaft:Mercedes-Benz Research and Development India Private LimitedStandort:Mercedes-Benz Research and Development India Private Limited, Bangalore Startdatum:sofortVeröffentlichungsdatum:..6Stellennummer:MER3PMNArbeitszeit:Vollzeit BewerbenAufgaben

Data Infrastructure & Operations

Offer flexible 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 options

· Handle federated access to cloud computing resource (or set of resources) based on a user's role within the organization

· Proficiency with Git, including branching/merging strategies, Pull Requests, and basic command line functions

· Proficiency in DevSecOps practices throughout the product lifecycle including fully managed Day 2 Ops leveraging Datadog

· Shared access controls to support multi-tenancy and self-service tooling for customers

· Manage data catalog per topic or domain based on services & use-cases offered

· Research, investigate and bring new technologies to continually evolve data platform capabilities

· Experience in working under Agile scrum Methodologies

Qualifikationen

Data Infrastructure & Operations

Offer flexible 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 options

· Handle federated access to cloud computing resource (or set of resources) based on a user's role within the organization

· Proficiency with Git, including branching/merging strategies, Pull Requests, and basic command line functions

· Proficiency in DevSecOps practices throughout the product lifecycle including fully managed Day 2 Ops leveraging Datadog

· Shared access controls to support multi-tenancy and self-service tooling for customers

· Manage data catalog per topic or domain based on services & use-cases offered

· Research, investigate and bring new technologies to continually evolve data platform capabilities

· Experience in working under Agile scrum Methodologies

Benefits Mit­arbeiter­rabatte möglich Gesund­heits­maß­nahmen Mit­arbeiter­handy möglich Essens­zulagen Betrieb­liche Alters­ver­sorgung Hybrides Arbeiten möglich Mobilitäts­angebote Mit­arbeiter Events Coaching Flexible Arbeits­zeit möglich Park­platz Betriebs­arzt Gute An­bindung Barriere­frei­heit Kinder­betreuung Kantine, Café

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