AKSHAY VUNUKONDA

Project 1

• Skilled in handling diverse telecom datasets from multiple countries, particularly focused on Tariffs
• Recharge Plans, CustomerDetails to deliver actionable insights for business stakeholders
• Implemented robust data ingestion pipelines using GCP services, particularly Big Query, to efficiently ingest and transform data fromvarious sources based on DIS
• Developed and maintained end-to-end data pipelines, utilizing a central data warehousing solution
• Implemented efficient Extract, Transform, Load (ETL) processes to handle large volumes of telecom data from multiple countries,ensuring data quality and reliability
• Proficient in designing and optimizing Big Query tables, queries, and jobs for optimal performance and cost- effectiveness, enablingtimely data analysis
• Implemented and managed Airflow workflows to automate the entire data pipeline from data ingestion to analysis, significantlyreducing manual intervention and enhancing operational efficiency
• Created Authorized views in Big Query to provide data to Down Streams
• Leveraged telecom domain knowledge to work extensively on recharge plans and other telecom-specific datasets, providing valuableinsights for business decision-making

Project 2

• Successfully migrated a telecom project from on-premise Hadoop to Google Cloud Platform (GCP), leveraging cloud services to achieve enhanced scalability, reliability, and cost-efficiency
• Developed and maintained data workflows and pipelines using Apache Airflow, orchestrating complex data processing tasks including data ingestion, transformation, and loading, leading to streamlined and automated data workflows
• Managed and processed large volumes of telecom data, including call detail records (CDR), subscriber information, network performance metrics, and recharge plans, ensuring data quality and integrity throughout the processing pipeline
• Implemented robust monitoring and alerting systems to proactively monitor the health and performance of
• Dataproc clusters and Airflow workflows, enabling timely detection and resolution of issues to minimize downtime
• Documented technical specifications, data workflows, and best practices for data engineering processes during the migration to GCP, ensuring knowledge sharing and adherence to industry standards and compliance requirements
• Proactively drove continuous improvement of data processing capabilities on GCP through workflow optimization and innovation in data engineering.

• Working experience in TWS Project to generate reports tailored to individual stocks using C#.Net
• Identifying and resolving database-related challenges and addressing environment issues affecting the task at hand.

Helios Project
Optimize banking operations by analyzing real-time data on ATM usage and branch traffic, leading to enhanced
service delivery.
Utilize Google Big Query as the central data warehouse for storing and analyzing real-time financial data, providing
scalable and cost-effective storage and processing capabilities.
Involved in Development of creating Data Pipeline to read the Data from Different sources and load data such as
transaction logs, customer details, and market data feeds to Big Query.
Responsible for creating the GCP buckets, Datasets, Big Query tables in different layers of BQ projects.
Worked on Creating DAG’s and tasks to deploy and run jobs in the Airflow scheduling tool.
Perform data processing and analysis using BigQuery's SQL-based querying capabilities, complex aggregations,
and advanced analytics on large datasets.
To find out root cause of the issue using Airflow logs and applies solution for the particular job.
Created Authorized views in Big Query to provide data to Down Streams (ML/Reporting/Analytics/Dashboards) for
enhancing decision-making capabilities