MB.OS-DataPlatform-Infra&DataOps Engineer-T94 Job Vacancy in Mercedes-Benz Research and Development India Private Limited Bengaluru, Karnataka – Updated today

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Full Details :
Company Name : Mercedes-Benz Research and Development India Private Limited
Location : Bengaluru, Karnataka
Position :

Job Description : Aufgaben
As a cloud engineer the candidate will contribute towards Product Development & Engineering of Self-Service Infrastructure tooling in the cloud for Big-Data and Analytics.

The created infra will 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.

What we do?
We build solutions that touches and defines the experience of more than 8 million Mercedes-Benz customers.We invest in building resilient and scalable solutions in the cloud using best development practices and state of the art cloud platforms.We endorse to “In God we trust; all others must bring data.” – W Edwards DemingWe believe if you build the best product then you don’t have to worry about waking up in the middle of the night to address an incident!We collaborate with colleagues from various delivery hubs of Daimler to deliver cutting edge in car experience for our customers.We own end-to-end delivery responsibilities and promote/adopt “You build it you run it” culture.We love polyglot programming and always choose the right technology and language to fit the need.
Technical Skills:

Rich experience with production-level development and operations on AWS or Azure Cloud.Experienced with Automation, configuration and provisioning infrastructure-as-code using Pulumi, Terraform, ARM in a controlled environment.Experienced in coding with Python, Bash, and/or Golang.Proficiency with CI/CD on deployment, management, and monitoring of applications.Proficiency in building a Scalable Data Platform for Big Data Use cases across Enterprise using Cloud technologies from Large providers, PaaS, Open source solutionsExpertise in data pipeline orchestration tools like Azure Data Factory,Amazon data Pipeline, Apache Spark/ Hadoop, DatabricksExperience on stream-processing systems: Kafka, Apache Storm, Spark-Streaming, Apache Flink, etc.Handling requirements of managed services, IAM, auto-scaling, High availability, elasticity, networking optionsProficiency with Git, including branching/merging strategies, Pull Requests, and basic command line functions.Experience in working under Agile scrum Methodologies.

Behavioral Skills:

Bias towards action/proactivity, shows initiativeBig picture thinking and understanding the business needsAs expected in Cloud space, curiosity learn and experiment new tech stacksAssertive communication & listening skills through various forums

Roles & Responsibilities:
Following are the areas of work but not limited to:
Designing, Building, Configuring, deploying, managing and automating next generation cloud infrastructure tools for interesting Automotive Big Data use cases ( Autonomous, Connected, Vehicle Diagnostics & many more)Building & operating Data Infrastructure for Data Driven Development, Data Driven operations and Monetization use cases across domainInteractively work with Data Engineering teams across locations(US,Germany,China etc.) to understand the requirements and build customised immutable self-service , secure and innovative infrastructure.Building shared access controls to support multi-tenancy and self-service tooling for customers.Federating access to cloud computing resource (or set of resources) based on a user’s role within the organization.Manage catalogue per topic or team based on services offered.Research, investigate and implement newer technologies to continually evolve security capabilities.Ensure successful delivery of application traffic across the cloud infrastructure.
Qualifikationen
Masters or Bachelor’s degree in computer science or relevant stream. Any proficient certification related to job are preferred.

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