Cloud Engineer - Data Infrastructure & DataOps
Experience - 4 - 8 years
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 Deming
• We 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.
Education & Certification
Masters or Bachelor’s degree in computer science or relevant stream. Any proficient certification related to job are preferred.
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 solutions
• Expertise in data pipeline orchestration tools like Azure Data Factory,Amazon data Pipeline, Apache Spark/ Hadoop, Databricks • Experience on stream-processing systems: Kafka, Apache Storm, Spark-Streaming, Apache Flink, etc. • Handling requirements of managed services, IAM, auto-scaling, High availability, elasticity, networking options
• Proficiency 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 initiative
• Big picture thinking and understanding the business needs
• As expected in Cloud space, curiosity learn and experiment new tech stacks
• Assertive 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 domain
• Interactively 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.