Mercedes Benz AG
SRE - Observability Expert
This job is now closed
Job Description
- Req#: 869544
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
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
About the company
Notice
Talentify is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.
Talentify provides reasonable accommodations to qualified applicants with disabilities, including disabled veterans. Request assistance at accessibility@talentify.io or 407-000-0000.
Federal law requires every new hire to complete Form I-9 and present proof of identity and U.S. work eligibility.
An Automated Employment Decision Tool (AEDT) will score your job-related skills and responses. Bias-audit & data-use details: www.talentify.io/bias-audit-report. NYC applicants may request an alternative process or accommodation at aedt@talentify.io or 407-000-0000.