Chandra Sai K Email & Phone Number

Mclean, Virginia, United States

Extensive experience in designing and implementing scalable data pipelines using Azure Data Factory, Databricks, and Synapse for ingesting and processing marketing data from platforms such as Google Marketing Platform, Salesforce MCI, and The Trade Desk.Proficient in configuring and administering marketing platforms, enabling seamless integration with internal databases and ensuring optimized data ingestion processes.Strong expertise in Azure and Google Cloud services, including ADLS Gen2, Power BI, and GCP BigQuery, for building and maintaining real-time marketing data analytics and reporting solutions.Skilled in developing automated data workflows using Python and PySpark in Databricks, reducing manual interventions and ensuring continuous data ingestion and transformation.Experienced in collaborating with cross-functional teams to gather requirements, implement secure data solutions, and deliver data-driven insights through dashboards and analytical tools like Power BI.Hands-on experience with performance monitoring, alerting, and troubleshooting of marketing data systems using Azure Log Analytics, ensuring operational efficiency and data integrity.Proficient in Agile methodologies, working within SAFe Agile frameworks to prioritize, design, and deploy solutions that meet business needs and performance SLAs.Expertise in building highly available, secure, and scalable data systems, leveraging cloud platforms (Azure, GCP) to support marketing initiatives and enhance decision-making through analytics.

Madison, Wisconsin, United States

Designed and developed data pipelines using Azure Data Factory to facilitate data ingestion from multiple marketing platforms such as Google Marketing Platform, Salesforce MCI, and The Trade Desk into cloud environments for real-time analytics and reporting.Collaborated closely with marketing teams to gather functional requirements and configure marketing platforms, ensuring smooth integration with internal systems for improved data flow and reporting.Implemented secure and scalable data ingestion pipelines to extract and load data between marketing platforms (Google Marketing Platform, Salesforce, ADvendio) and cloud-based storage solutions such as Azure Data Lake Storage (ADLS Gen2) and Google Cloud Storage (GCP).Administered and configured marketing platforms to optimize data extraction and ingestion processes, ensuring seamless synchronization between marketing systems and internal databases.Developed and maintained dashboards using Power BI, visualizing marketing data from platforms like Salesforce and The Trade Desk, providing business insights to stakeholders.Utilized Azure Synapse and Databricks for data transformation and large-scale data processing, enabling advanced analytics on marketing data ingested from multiple platforms.

Philadelphia, Pennsylvania, United States

-Worked on Big Data Hadoop cluster implementation and data integration in developing large-scale system software.-Design and Develop ETL Processes in AWS Glue to migrate Campaign data from external sources like S3, ORC/Parquet/Text Files into AWS Redshift.-Involved in Analysis, coding, testing, user acceptance testing, production implementation, and system support for the Enterprise Data Warehouse Application.-Developed the architecture of the data pipeline for data analysis.-Evaluated the suitability of Hadoop and its ecosystem to the above project and implemented/validated with various proof of concept (POC) applications to eventually adopt them to benefit from the Big Data Hadoop initiative.-Scala Script to load processed into DataStax Cassandra 4.8.-Transformed the AB initio Process into Hadoop using PIG and HIVE.-Prepared migration strategy for data ingestion from legacy platforms to HDFS.-Map-Reduce Job to compare two files TSV and save the processed output into Oracle.-Used Informatica Manager for managing the Informatica repository to define custom routines & transforms, import and export items between different Informatica systems, or exchange metadata with other data warehousing tools.

Hyderabad, Telangana, India

-Handled Responsibilities likes managing and monitoring the Hadoop cluster with Cloudera Manager.-Handled massive data sets in parallel across the Hadoop cluster, I have created a MapReduce application in Java using the MapReduce programming framework.-Acquired practical knowledge of Amazon Web Services' (AWS) infrastructure S3 and EC2 are two of Amazon’s cloud services (Amazon EC2).-Developed Sqoop scripts to import, export, update the data between HDFS/Hive and Relational Databases.-Used Hive Queries to get information stored in HDFS and the Hive Warehouse.-Involved in Directed Acyclic Graph (DAG) of operations and control flows, defined by Oozie for scheduling tasks to manage Apache Hadoop workloads.-Created Spark apps in Scala, packaging them in jars, and running them on a cluster.-Optimized data processing times by creating Spark core and Spark SQL scripts in PySpark.-Worked on managing and reviewing the Hadoop log files.-Transformed the data from online transaction processing to online analytical processing, a thorough ETL design was developed.-Worked on documentation like including a Source-to-Target Data Mapping Document, a Set of Unit Test Cases, and a Set of Data Migration Documents.-Using SparkSQL and other PySpark libraries, worked on Data Exploration to analyze patterns and select features.-Analyzed, discovered, and fixed many Python problems in the two key applications utilized by the company's clients and customer service workers.-Managed and reviewed Hadoop Log Files, deploying and Maintaining Hadoop Cluster-Responsible for cluster maintenance, adding and removing cluster nodes and cluster monitoring.-Loaded and transformed large amounts of structured, semi-structured, and unstructured data into the Hadoop system.-Used Spark to handle streaming data and did sophisticated analytics while processing.

Master'S Degree, Information Technology

Bachelor'S Degree, Electrical, Electronics And Communications Engineering