Must have experience with similar platform engineering/management solutions: Building/optimizing Data LakeHouse with Open Table formats Kubernetes deployments/cluster administration Transitioning on-premise big data platforms to scalable cloud-based platforms like AWS Distributed Systems, Microservice architecture, and containers Cloud Streaming use cases in Big Data Ecosystems (e.g., EMR, EKS, Hadoop, Spark, Hudi, Kafka/Kinesis) Must have hands-on experience with below tech stack: Must have experience with below tech stack: Git Hib and Git Hub Actions AWS o IAM o API Gateway o Lambda o Step Functions o Lake formation o EKS & Kubernetes o Glue: Catalog, ETL, Crawler o Athena o Lambda o S3 (Strong foundational concepts like object data store vs block data store, encryption/decryption, storage tiers etc) Apache Hudi Apache Flink PostgreSQL and SQL RDS (Relational Database Services). Python Java Terraform Enterprise o Must be able to explain what TF is used for o Understand and explain basic principles (e.g. modules, providers, functions) o Must be able to write and debug TF Helpful tech stack experience would include: Helm, Kafka and Kafka Schema Registry, AWS Services: CloudTrail, SNS, SQS, CloudWatch, Aurora, EMR, Redshift, Iceberg, Vault, AWS Secrets manager