Core Responsibilities
- Design and optimize batch/streaming data pipelines using Scala, Spark, and Kafka
- Implement real-time tokenization/cleansing microservices in Java
- Manage production workflows via Apache Airflow (batch scheduling)
- Conduct root-cause analysis of data incidents using Spark/Dynatrace logs
- Monitor EMR clusters and optimize performance via YARN/Dynatrace metrics
- Ensure data security through HashiCorp Vault (Transform Secrets Engine)
- Validate data integrity and configure alerting systems

Requirements
- Programming :Scala (Spark batch/streaming), Java (real-time microservices)
- Big Data Systems: Apache Spark, EMR, HDFS, YARN resource management
- Cloud & Storage :Amazon S3, EKS
- Security: HashiCorp Vault, tokenization vs. encryption (FPE)
- Orchestration :Apache Airflow (batch scheduling)




- Operational Excellence Spark log analysis, Dynatrace monitoring, incident handling, data validation

Mandatory Competencies
- Expertise in distributed data processing (Spark on EMR/Hadoop)
- Proficiency in shell scripting and YARN job management
- Ability to implement format-preserving encryption (tokenization solutions)
- Experience with production troubleshooting (executor logs, metrics, RCA)

Benefits

Benefits

Insurance - Family​
Term Insurance
PF
Paid Time Off - 20 days
Holidays - 10 days
Flexi timing
Market-competitive salary
Diverse & Inclusive workspace

📌 Big Data Engineer (Hyderabad)
🏢 Kmccorp India
📍 Hyderabad