Saikrishna P Email & Phone Number

Cincinnati, Ohio, Us

•Built efficient data pipelines in Azure Data Factory and Databricks, increasing data throughput by 40%.•Developed big data solutions with Azure Synapse, using T-SQL and Python to improve data analysis.•Architected BI solutions with Azure Data Lake, enhancing data access for healthcare analytics.•Optimized ETL processes with PySpark in Azure Synapse, boosting data processing efficiency by 35%.•Managed real-time data streaming with Kafka and Spark, ensuring high data quality.•Secured data transfers from SQL Server to SFTP using Azure Databricks workflows.•Designed Snowflake data integration with PySpark, improving data management.•Enhanced data visualization with Alteryx and SQL for Tableau Server.•Monitored system health using the ELK Stack and automated Azure provisioning with Terraform, reducing setup time by 20%.

Dublin, Oh, Us

•Managed secure AWS VPC configurations for mortgage processing, ensuring robust data operations.•Built and optimized ETL pipelines with Pig and Sqoop, transferring data from UNIX to HDFS for advanced analytics.•Used Elasticsearch and Kibana to visualize real-time analytics, providing stakeholders with actionable insights.•Monitored Spark Databricks clusters and optimized data manipulation using Spark DataFrame API, improving precision by 40%.•Improved data transfer efficiency on AWS using SSIS and DTS for database import/export.•Streamlined application deployment with Docker and Apache Mesos, ensuring consistency across finance applications.•Enhanced CI/CD workflows with Jenkins, reducing deployment issues by 15%.•Managed CI/CD pipelines with Jenkins and OneOps, streamlining mortgage data processing for more accurate reporting.

Kista, Stockholm, Se

•Leveraged Google Cloud (GCE, Storage, VPC, IAM) for secure, scalable data handling in finance.Built Data Studio reports for billing insights, optimizing costs.•Tuned Spark for real-time analytics, improving transaction processing.•Deployed Spark-SQL in Databricks for ETL, revealing customer usage patterns.•Created PySpark apps for batch and stream processing, supporting SaaS decisions.•Managed data pipelines with Python and Azure Data Factory for accurate reporting.•Used Sqoop and Cloud Dataproc for efficient data ingestion into GCP.•Ran GCP Dataflow for streaming/batch jobs, analyzing data in BigQuery.•Enhanced ETL speed by 70% with MapReduce and Airflow.•Integrated on-prem SQL with Azure Analysis Services, streamlining Power BI reporting.•Coordinated data ingestion in Databricks, generating ad-hoc BigQuery reports.•Visualized insights with Tableau and Python Seaborn for data analysis.

Mumbai, Maharashtra, In

•Automated data ingestion with AWS CodePipeline and workflows, boosting efficiency by 20%.•Leveraged dbt, Lambda, and SQS for agile ETL, improving data flow and turnaround times.•Validated and reconciled ETL metadata, ensuring high data integrity.•Loaded data from Oracle and Teradata to HDFS using Sqoop for enhanced analytics.•Achieved 80% data completeness through Python-based validations and cleaning.•Built Hive tables with dynamic partitions for consumer analysis, aiding targeted marketing.•Implemented Kafka and Spark Streaming for real-time payment insights.•Developed Databricks ETL pipelines with Spark, enhancing data transformation by 35%.•Used Airflow and Lambda for automated, reliable job scheduling.•Optimized data retrieval with complex MySQL queries via Python connectors.

Master'S Degree, Computer Science

Bachelor Of Technology - Btech, Computer Science