Senior Data Platform Engineer — Cloudera, AWS & Kubernetes

The mission

We are looking for a battle-tested Data Platform Engineer who can build, operate, troubleshoot, and evolve large-scale data platforms across on-premises Cloudera settings and cloud-native AWS/Kubernetes architectures.

This is not a dashboard or SQL-only role. You will work where distributed compute, storage, networking, Kubernetes, and production data pipelines meet. You must be comfortable tracing a failed workload from the application layer through Spark or Flink,
Kubernetes operators, HDFS/Hive, infrastructure, and AWS services.

The goal is to help us evolve safely from on-premises, VM, and EC2-based platforms into resilient, observable, cloud-native data systems.

What you'll do
Build and operate production data platforms across Cloudera on premises, Cloudera cloud environments, AWS EMR, and Kubernetes.
Design batch and streaming pipelines using Spark, Flink, Hive, and related technologies.
Transform large datasets through filtering, sorting, joining, aggregation, partitioning, enrichment,



and restructuring.
Work with Parquet, Avro, JSON, CSV, and other delimited or semi-structured formats.
Design storage, partitioning, compression, retention, and lifecycle strategies across HDFS, Hive, and object storage.
Design and maintain Hive schemas, tables, partitions, metadata, and data models.
Administer Cloudera clusters, including installation, upgrades, configuration, scaling, patching, security, backup, and recovery.
Troubleshoot unhealthy services, failed jobs, resource contention, data skew, small-file problems, metadata issues, and storage bottlenecks.
Tune Spark and Flink workloads for memory, CPU, parallelism, shuffle behavior, checkpointing, and recovery.
Operate AWS services such as EMR, S3, IAM, EC2, EKS, CloudWatch, KMS, and supporting networking services.
Deploy and operate data workloads on Kubernetes using operators, Helm, custom resources, and GitOps-bas

📌 Senior Data Engineer Bengaluru (India)
🏢 Tookitaki Holding
📍 India