MB.OS 2.0 Data Infrastructure & Operations Professional

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

• 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.