May 2023 – Present · 2 yrs 10 mos

• Lead team of 10 strong engineers for Paragon Case Management Insights (PCMI) Data Platform, which is used for interactions with Amazon’s business partners, including, but not limited to, Sellers and Vendors. PCMI Data Platform team empowers Amazon’s Selling Partner Support Experience, Root-cause and Case Management tenants to make data driven decisions and derive insights. Key areas of my job responsibilities in this role include:
• Drive flagship VP level goals and company-wide cross cutting initiatives with tight dealines.
• Define strategic decisions like 3-year vision for the team by collaborating with senior leaders in the organization across engineering and product disciplines with willingness to challenge the status quo.
• Evaluate scope, dependencies and priority to effectively collaborate with key stakeholders to find a path forward in ambiguous situations.
• Impact growth and development of team through mentorship, coaching, and identifying other growth opportunities.
• Establish structures and mechanism in the team to expand knowledge base, solve complex problems and deliver results.
• Clearly communicate performance of team members. Align team’s progression of delivering goals to their growth and development in relevant skills. Participate in calibration activities so that your evaluation is fair and accurate.
• Design to develop data products, infrastructure and data pipelines leveraging Cloud services. Drive the adoption of new technologies (e.g AWS, Gen AI) and best practices.
• Lead design reviews to with Principal engineers and Business stakeholders to solve problems of scale and build highly scalable, flexible and resilient cloud architectures.
• Drive process improvements, operational excellence, and best practices in the team

Apr 2021 – May 2023 · 2 yrs 1 mo

• As Senior Solution Architect, I have worked with AWS customers to design and build big data analytics and database solutions through AWS Data Lab program. I provide prescriptive technical guidance to AWS customers on AWS services, thereby accelerating their path to production.
• Throughout my tenure as Senior Solution Architect, I have been seeked out for my technical experience as subject matter expert or speaker at internal and external customer events. I have been recognized as a thought leader within AWS Data Lab team, for leading end-to-end content and delivery of "Data Lab Academy" program to onboard new hires across the globe. My work on standardization of interview calibration guide for Data Lab Architects, has been appreciated at director level in my org.

Sep 2019 – Apr 2021 · 1 yr 7 mos

• Lead engineering customer engagements with tangible deliverables to accelerate data and analytics modernization initiatives on AWS technologies.
• Worked with teams to deliver highly available, low latency services by gathering requirements, performing data modeling, designing and implementing rapid prototyping of software solutions using AWS services in database and analytics space.
• Performed rapid troubleshooting of complex technical problems as well as accurately assess and mitigate risks by conducting performance tuning, backup/recovery planning, and scalability/capacity planning
• Developed long-term database and analytics technology strategies that significantly influence cross-company database and data engineering processes and standards.
• Established standards to maintain security and integrity controls for software solutions, and provide best practices for monitoring policies, procedures, and standards relating to data management by establishing and calculating optimum values for database parameters and user access levels.
• Extensively worked on AWS Glue Service for data preparation, data transformation and data ingestion to build ETL prototyping solutions.
• Collaborated with AWS Service teams to identify gaps in database and analytics AWS services.

Nov 2017 – Sep 2019 · 1 yr 10 mos

• As a Database Engineer at Amazons’ Finance Technology line of business, I managed Oracle Financial Application production environment by providing support to and administering multiple Oracle databases, including RAC clusters for performance critical, highly available, massively concurrent, distributed systems. I also worked extensively on migration of vendor payment systems from Oracle to Amazon Aurora in AWS.
• Provided support to various layers of databases down to system architecture, operating systems, and hardware, storage, and network configurations.
• Worked with the software development team to deliver highly available, low latency services by gathering requirements, modeling, designing, developing, testing, implementing, supporting, and tuning high availability data.
• Assisted in developing long-term department database technology strategies that significantly influence cross-company database engineering processes and standards.
• Established and maintained security and integrity controls, and formulated monitoring policies, procedures, and standards relating to data management by establishing and calculating optimum values for database parameters, and specifying users and user access levels.
• Provided support for system upgrades and new system releases, and performed database monitoring, security monitoring, troubleshooting, and resolution of system failures.
• Worked extensively on proof of concept and later production migration of terabyte scale Oracle to Amazon Aurora PostgreSQL migration of critical Vendor Payments Systems.
• Extensively worked on AWS Database Migration Service and Amazon Schema Conversion Tool
• Created multiple feature requests to AWS Data Migration Service team service team based on the gaps identified in the service during migration and worked closely with AWS Support team.

Sep 2016 – Nov 2017 · 1 yr 2 mos

Feb 2013 – Sep 2016 · 3 yrs 7 mos

• Amazon’s data-warehouse system is huge as of Petabytes scale and the business intelligence applications run on top of it to provide insights to end users about the sales of their products and do further analysis. This is a centralized data-warehouse for complete Amazon, with huge RAC systems with nodes scaling upto 32 per cluster. Some of the daily activities that I worked on as part of this project are as follows:
• AWS Redshift Database: Took lead in understanding redshift database technology and migration of oracle database in redshift. Became SME in the same and helped other teams in their migrations as well. Partnered on migration of clickstream data to Amazon Redshift, which required migration on 100 node Redshift Cluster - Largest cluster ever used at Amazon.
• Worked on Python programming for building automations around AWS Services like AWS Lambda, AWS S3 for maintenance of AWS Redshift databases.
• Worked on DB and grid upgradation projects on RAC systems from 11gR1 to 11gR2.
• Supported RAC database upto 32 nodes in the environment. Worked on troubleshooting in case of node evictions.
• Supported 12X7 On Call activities on production systems.
• Worked on providing partitioning solutions in the data-warehouse systems for tables as huge as 200TB.
• Created multiple scripts in PL/SQL to provide solutions and monitoring alerts for databases of Petabyte scale.
• Worked on improving load and extract job performance on the database through performance tuning techniques.
• Acquired knowledge on Hitachi and EMC storage arrays, to dig down into I/O issues in the system.