I am a Data Architect with 10 years of international experience in software development, data engineering, big data and AWS Cloud. I specialize in developing and implementing scalable, reliable, and secure data architectures that enable organizations to make informed decisions based on their data assets. My experience spans multiple domains, including e-commerce, retail and fintech.
Total Professional experience: 10 years 2 months –
1) 1 month (April 2023 – Present)
Company : Chewy (https://chewy.com/)
Position – Senior Data Architect:
2) 5 Year 3 Months ( Dec 2017 – March 2023)
Company – Amazon Web Services (https://aws.amazon.com/)
Position – Data Architect, Data Lake
3) 9 Months ( Feb 2017 – Dec 2017)
Company – Orzota Inc.
Position – Big Data Engineer
4) 1 Year (Jan 2016 – Dec 2016)
Company – Leap Doctor Tampa
Position – Software Engineer
5) 2 Years 8 Months (Nov 2012 – July 2015)
Company – Tata Consultancy Services
Position – Sr. Systems Engineer
Skills –
1) Big Data Expertise: Proficient in handling large datasets and leveraging big data technologies such as Hadoop, Spark, and Kafka to process, analyze, and manage vast amounts of structured and unstructured data.
2) AWS Analytics Services: Comprehensive understanding and hands-on experience with AWS analytics services, including Amazon Redshift, Amazon Kinesis, Amazon EMR, AWS Glue, and Amazon QuickSight, to provide scalable, flexible, and cost-effective data solutions.
3) Data Modeling and Design: Expert in designing and implementing data models, schemas, and ETL processes to ensure optimal performance, scalability, and data integrity across various data storage and processing platforms.
4) Data Warehousing: In-depth knowledge of data warehousing concepts, including star schema, snowflake schema, and dimensional modeling, to support efficient data storage and retrieval for business intelligence and reporting purposes.
5) Database Management: Proficient in managing relational and non-relational databases, such as MySQL, PostgreSQL, Oracle, MongoDB, and Amazon DynamoDB, ensuring high availability, fault tolerance, and optimal performance.
6) Data Integration: Skilled in integrating data from various sources, including APIs, flat files, and databases, using tools such as Apache Nifi, Talend, and AWS Data Pipeline.
7) Data Security and Compliance: Strong understanding of data security best practices and compliance regulations, such as GDPR and HIPAA, to ensure the highest level of data protection and privacy for customers and stakeholders.
8) Cloud Architecture: Well-versed in designing and deploying secure, scalable, and cost-effective cloud-based data solutions using AWS services, such as Amazon S3, AWS Lambda, and Amazon API Gateway.