Sai Deep Email & Phone Number

United States

• Created Function as a service is a category of cloud computing services that provides a platform allowing customers to develop, run, and manage application functionalities without the complexity of building and.
• Implemented a 'serverless' architecture using API Gateway, Lambda, and Dynamo DB and deployed AWS Lambda code from Amazon S3 buckets.
• Developed and maintained applications using Java, JavaScript, and Python, creating efficient data processing solutions and backend services for enterprise-scale logistics operations at UPS.
• Implemented CI/CD pipelines using AWS Code Pipeline and Code Build for automated deployment of AWS Lambda functions.
• Experience integrating AWS services (e.g., S3, Lambda, DynamoDB) using the AWS SDK for JavaScript, enabling seamless cloud interactions within JavaScript applications.
• Partnered closely with Engineering stakeholders to gather requirements, understand project objectives, and design scalable data pipelines needs.

Dallas, Texas, United States

• Extensive working experience in working Microsoft Azure and Hadoop Cloudera Distribution platform.
• Designed and implemented ETL pipelines using AWS Glue to extract, transform, and load data from various sources into data lakes and warehouses.
• Implemented a 'serverless' architecture using API Gateway, Lambda, and Dynamo DB and deployed AWS Lambda code from Amazon S3 buckets.
• Developed Airflow DAGs to schedule and automate end-to-end data pipelines, enabling the seamless execution of daily batch processing tasks and improving overall data pipeline efficiency
• Implemented best practices for managing DynamoDB tables, including partition management, data retention policies, and backup and restore strategies.
• Integrated Kinesis with various AWS services (e.g., S3, Lambda) to create a seamless data pipeline for ingesting and storing streaming data, enhancing overall data architecture.

Arlington, Texas, United States

• Orchestrated the deployment of containerized data processing workflows using Google Kubernetes Engine (GKE), improving resource utilization and scalability.
• Developed and optimized complex SQL queries in BigQuery, reducing query execution times and improving overall performance.
• Experience with converting Teradata schemas, tables, and views to equivalent structures in GCP, particularly BigQuery.
• Designed and implemented hybrid database solutions combining NoSQL and SQL databases to leverage the strengths of both technologies for specific application needs.
• Built pipelines to transfer and transform large datasets stored in Google Cloud Storage into Snowflake, leveraging Snowflake’s native connectors.
• Utilized Talend to integrate diverse datasets for Texas Health Care, including clinical and operational data, ensuring seamless data flow between disparate systems and the data warehouse.

California, United States

• Involved in developing batch and stream processing applications that require functional pipelining using Spark APIs.
• Developed Databricks notebooks for data preparation i.e. data cleansing, data validation, et cetera and applied transformations as per our requirement
• Involved in building a data pipeline and performing analytics using AWS stack (EMR, EC2, S3, RDS, Lambda, SQS, Redshift).
• Developed Sqoop jobs for data ingestion, incremental data loads from RDBMS to HDFS.
• Utilised Spark’s in memory capabilities to handle large datasets on S3 Data lake. Loaded data into S3 buckets, then filtered and loaded into Hive external tables..
• Involved in developing a custom-built Rest API to support real time customer analytics for data scientists and applications.

Hyderabad, Telangana, India

• Involved in import and export of data between Hadoop Data Lake and Relational Systems like MySQL, Oracle usingSqoop.
• Working knowledge on creating Kafka topics, partitions and writing custom partitioners classes.
• Experienced in writing Spark applications in Python (Pyspark).
• Made use of the AWS environment to launch the applications in different regions and implemented CloudFront with AWS Lambda to reduce latency.
• Worked and acquired a lot of knowledge in Amazon Web Services (AWS) cloud services like EC2, S3, EMR, EBS, RDS and VPC.
• Extracting real time data using Kafka and Spark streaming by Creating D streams and converting them RDD, processing it and storing it into Cassandra.