Tata Consultancy Services
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Bengaluru · On-site · 6-9 Yrs · Oct 11
Software Development · 10000+ Employees · Mumbai, India
Hiring: Engineering
What employees say
+ Good work life balance and nice work environment.
− Low hike not more than 7%
More reviews on the company profile.
Interview experience · Data Analyst
2 rounds. 1st round technical power bi and sql like cumulative total. What data sources you used. few scenario based questions, remove duplicate in sql. Optimization of slow performing report
Average difficulty · India · 22,544 reports
More interview insightsJob description
Overview
EKS & Spark Performance Optimization Engineer
Responsibilities
- Design, implement, and optimize big data processing solutions on AWS.
- Manage and optimize workloads running on Amazon EKS and Amazon EMR.
- Perform Spark application performance tuning, troubleshooting, and capacity planning.
- Analyze Spark jobs and optimize resource allocation, memory management, executors, and partitioning strategies.
- Enhance cluster utilization, scalability, reliability, and cost efficiency.
- Monitor and troubleshoot production workloads running on Kubernetes and EMR environments.
- Implement best practices for containerization, orchestration, and cloud-native deployments.
- Collaborate with data engineers, architects, and platform teams to improve application performance.
- Optimize AWS infrastructure for high-performance distributed computing workloads.
- Create operational dashboards, monitoring solutions, and performance reports.
Qualifications
- Location: PAN India
- We are seeking a highly skilled EKS & Spark Performance Optimization Engineer with strong expertise in AWS cloud technologies, Amazon EKS, EMR, and Apache Spark performance tuning. The ideal candidate will be responsible for optimizing large-scale data processing workloads, improving cluster efficiency, reducing execution costs, and enhancing application performance in cloud-native environments.
- Strong hands-on experience with Amazon EKS (Elastic Kubernetes Service).
- Expertise in Apache Spark performance tuning and optimization.
- Experience with Amazon EMR and large-scale data processing workloads.
- Strong understanding of distributed computing concepts and cluster management.
- Experience troubleshooting Spark job failures, memory issues, and performance bottlenecks.
- Amazon EKS
- Amazon EMR
- EC2
- CloudWatch
- IAM
- VPC
- AWS Cost Optimization
- Spark SQL Optimization
- Executor and Driver Tuning
- Partitioning and Caching Strategies
- Shuffle Optimization
- Resource Allocation and Cluster Sizing
- Job Monitoring and Troubleshooting
- JVM Performance Tuning
- Performance Benchmarking
- Kubernetes
- Docker
- CI/CD Pipelines
- Infrastructure as Code (Terraform/CloudFormation preferred)
- Monitoring and Observability Tools
- Experience with Databricks or AWS Glue.
- Exposure to Hadoop ecosystem components.
- Knowledge of Airflow or other workflow orchestration tools.
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Job application FAQ
Last updated 27 October 2026
- How do I apply for EKS with Spark Tuning at Tata Consultancy Services?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Tata Consultancy Services may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this EKS with Spark Tuning role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is EKS with Spark Tuning remote or on-site in Bengaluru, Karnataka?
- This listing is marked on_site with location Bengaluru, Karnataka. Confirm details on the job description before applying.
- What skills matter for this EKS with Spark Tuning role at Tata Consultancy Services?
- Key skills for this role include skills listed in the job description. Upload a resume to see which requirements you already meet and which are gaps.