Dec 2021 – Sep 2024 · 2 yrs 9 mos · Hyderabad, Telangana, India · Hybrid

• Primarily working as Cloud Platform Engineer for client - Apple Inc.
• Build and manage BigData platform in Cloud to store and process petabytes of data.
• Created and deployed cloud stacks like storage and compute based on application requirements
• Debug, locate and resolve production issues, errors by analysing logs from kube Pods, Splunk, Cloudwatch
• Manage cloud computing resources running on multiple AWS accounts
• Work closely with different teams to build, deploy and integrate resources into cloud seamlessly
• Automate infrastructure deployment using IaaS tools like Cloudformation, Pulumi
• Created detailed runbooks for SOPs
• Worked on Apache Yunikorn scheduling
• EKS Cluster setup, validation, updgradation
• Worked on AWS Cost optimisation:
• S3: life cycle policies
• Ec2: EBS Volume migration and stale volume cleanup
• TMS: Optimisation and snapshot/orphan cleanup
• Impact:
• Prod environment monthly cost reduced by ~25%.
• Created cloud data lakes on AWS and pipelines to ingest data across these systems.
• Deploying S3 buckets, IAM roles, EKS cluster using AWS CLI, Cloudformation, Pulumi
• Migration to cloud data lakes from on-prem clusters
• Reproducing, Analysing and Troubleshooting related to AWS access
• Working on CI/CD pipelines to automate the infrastructure provisioning in cloud services like AWS
• Manage EMR and EKS clusters in terms of Uptime, Health, Performance, and Compliance.
• Tuning and monitoring the ETL/ELT data pipelines, so that data will be flowed smoothly without any interruptions.
• Graviton EC2 instance testing and deployment
• Multiple repo/module management in GIT
• Querying and building dashboards in Splunk for analysing the logs
• Mentored and groomed new team members and provided extensive KT
• Provided on-call rotations/support over weekends based on shift calendar

Jun 2019 – Dec 2021 · 2 yrs 6 mos · Hyderabad, Telangana, India · Hybrid

• Primarily working as Cloud and Data Platform Engineer for client - Apple Inc.
• Hadoop Platform On-Prem cluster management spanned over 3 Data Centers
• Multiple Clusters with over 1200 nodes, ~40 Petabytes of storage per cluster.
• Monitor Health / Track utilisation trends to meet Storage and Computational needs.
• Proof of Concepts (on emerging Hadoop ecosystem tools).
• Migration to Kubernetes from on-prem clusters
• In depth understanding of spark internal architecture like drivers, executors, joins, shuffles, DRA
• Reproduce, analyse and solve issues in spark and Hadoop for jobs running in production
• Work closely with Application Teams to help them migrate from Hive to Spark and solve any issues, if having when writing their jobs
• Assist Application teams to fine tune their spark SQL queries to make sure they run effectively in production without using any extra memory configs
• Improve performance of newly deployed spark applications in prod without changing any memory configurations
• Perform RCA on failed jobs in production and test clusters
• Document usage guides/best practices/issues in Spark
• Validate large production clusters after any changes/upgrades
• Parse JSON data to readable format and storing in tables
• Retrieve actual memory utilisation of applications in production clusters using SPARK SQL
• Create dashboards in Zeppelin to visualise the monitoring data and draw meaningful insights from it
• Write Splunk queries to extract required data and build graphs from logs for debugging.
• Managing all deployed code into GIT
• Deployed and supporting all documentation in an internal Web site

May 2018 – Jul 2018 · 2 mos · Jaipur, Rajasthan, India

• First Legal Aid | LinuxWorld Informatics Pvt. Ltd.
• Developed a product, "First Legal Aid" that aims to provide a solution to different types of real-life legal scenarios in which an individual faces.
• Assist users based on cases that had been reported in the past, which have a similar context and advises about the best possible legal action.
• Different datasets stored in Hadoop cluster and analyzed on the MapReduce cluster will be used to train the machine learning model. This model will then, analyze and predict the accurate solutions based on their legal queries.
• Docker | Ansible | Hadoop | Python CGI
• Ansible: Automated Cloud Computing services and Hadoop MapReduce cluster setup on different nodes/terminals.
• Provide cloud services such as SaaS, PaaS, CaaS, STaaS, etc.
• Developed a Minimal Web Framework in Python-CGI with features such as Template Support, Session Management using Cookies, etc.
• Data Analysis: Clearing and filtering data from datasets using Pandas and Numpy, and plotting real-time insights on the webpage using Matplotlib, Seaborn, Cufflinks and Plotly.
• Additional features include Face-Recognition (Using pre-trained CNN), Speech Synthesis and Recognition (Using JS libraries - Annyang and SpeechKITT)

Dec 2017 – Feb 2018 · 2 mos · Work from home · Remote

• Learnt the basic principles and tools used in the financial markets technical analysis and applied them in the Indian Stock Markets.
• Got hands on experience on trading platforms like FXCM tradestation, tradeview.