Oct 2021 – Present · 4 yrs 6 mos · Amsterdam

Sep 2020 – Sep 2021 · 1 yr · Noida, Uttar Pradesh, India

Aug 2020 – Sep 2020 · 1 mo

Jul 2018 – Jul 2020 · 2 yrs · Gurgaon, India

• Service Line: Analytics and Cognitive
• Client Description:
• Client is an American mass media corporation. The company has also been involved in internet radio and podcasting via the digital platform available across more than 250 platforms and 2,000 devices including smart speakers, digital auto dashes, tablets, wearables, smartphones, virtual assistants, TVs and gaming consoles. Clients want to retire their GCP bigdata platform and go live on AWS, RE-MODERNIZE.
• Role: Tech Specialist/ Individual contributor
• Key Responsibilities:
• Perform Code analysis on Airflow DAG and migrate same to AWS framework compatible code by making use of python, docker, AWS Glue, Redshift, Lambda, SQS.
• Conduct due diligence to keep intact functionality of existing code while migrating to AWS
• Provide coding standard checklist to team (i.e. pylint, isort, black, bandit, flake, radon, pyflakes)
• Utilize AWS equivalent services w.r.t to GCP while migrating (i.e. S3, SQS, lambda, step function, CloudWatch, glue, Athena, Redshift, ECS, SSM, Secret Manager, CFT, Code Pipeline)
• Understand and enhance DevOps pipeline to deploy code to higher environment (DevOps tool used – Sceptre)
• Use GIT for version control and deployment.
• Client Description:
• Client was Japanese multinational automotive manufacturer headquartered in Japan. Clients want to become a data exchange player in coming year and wanted Deloitte to build a road map to accomplish.
• Key Responsibilities:
• ⦁ Perform analysis on the Data Exchange players across the Use Cases and other Data Exchange players in the market for each target sectors to identify common capabilities
• ⦁ Conduct due diligence to identify feature offered by each DX player in the market
• ⦁ Built conceptual architecture diagram with all the futuristic capabilities.
• ⦁ Worked on preparing sector agnostic technical architecture compatible with both AWS and Azure.

Aug 2015 – Jun 2018 · 2 yrs 10 mos · Bengaluru Area, India

• ETL Developer and Hadoop Developer has a strong background with file distribution systems in a big-data arena. Understands the complex processing needs of big data and has experience developing codes and modules to address those needs.
• Good experience with Sqoop, Oozie, HBase and Hive.
• Solid understanding of the Hadoop file distributing system
• Capable of processing large sets of structured, semi-structured and unstructured data and supporting systems application architecture.
• In-depth understanding of Map-Reduce and the Hadoop Infrastructure
• Developed ETL Jobs, perform Unit Testing and Performance Tuning

Jan 2015 – Aug 2015 · 7 mos · Bengaluru Area, India

• Work with Data Modeller’s and Business Analyst to understand Mapping and Business needs.
• Creating Technical Specification Document based on the provided Mapping document.
• Developing ETL Jobs , perform Unit Testing.
• Analyzing the Data Issues raised by business report users and performing code fix if required.
• Supporting System Integration Testing and User Acceptance Testing for resolving defects.
• Tuned the Datastage jobs for better performance.

Nov 2010 – Dec 2014 · 4 yrs 1 mo

• Working on Cognos Tools like–Cognos (8.4), Cognos (10) (Report Studio, Analysis Studio, Framework Manager)
• Knowledge of Data Stage client tools v7.5 and v8.1 - Data Stage Designer, Data Stage Manager, and Data Stage Director.
• Involved in Developing Reports using Report Studio and Query Studio as per the business requirements.
• Created different kinds of reports including List, Cross-tab, Charts, Conditional Block, Prompts.
• Scheduling and distributing reports through schedule management in Cognos Connection.
• Good knowledge of PL/SQL, DB2 and UNIX
• Experience and expertise in understanding existing business processes, data analysis requirements, business systems analysis and design, converting requirements specifications into functional specifications
• Ensuring SLA management for the process.