Shreya P Email & Phone Number

Des Moines, Iowa, United States

As a data engineer, I have developed and managed ETL workflows using AWS Data Pipeline, AWS Glue, and Informatica PowerCenter, ensuring efficient data integration and processing for large datasets. My expertise includes designing scalable data pipelines, integrating diverse data sources into data warehouses, and optimizing data processing through tools like Talend and Matillion.I have extensive experience with Apache Spark, implementing PySpark jobs and developing data ingestion workflows using Sqoop and Flume. My focus on performance optimization and fault tolerance has enabled me to architect complex ETL pipelines with Apache Airflow, while also managing SQL Server instances and migrating databases to Snowflake and Redshift.In addition to technical development, I have created interactive Power BI dashboards, provided training on best practices, and implemented CI/CD workflows using GitHub Actions. My commitment to documentation and process improvement has facilitated smoother deployment and enhanced collaboration across teams

New York, United States

I have extensive experience designing and implementing data integration solutions using Azure Data Factory, orchestrating and automating ETL processes to manage data storage and analytics with Azure Data Lake Storage and Azure Synapse Analytics. My focus on data accuracy includes implementing validation and cleansing processes within ETL workflows, optimizing performance across various platforms like Informatica and Talend.I have successfully developed and maintained scalable ETL pipelines using technologies such as Matillion, PySpark, and SQL. My expertise extends to integrating Hadoop with Spark and Hive to enhance data processing capabilities, as well as leveraging Snowflake’s native tools for effective data warehousing. I’ve also implemented machine learning models in production environments, ensuring seamless integration with existing systems.In addition to technical skills, I’ve managed CI/CD pipelines using GitHub, administered GitLab repositories, and utilized Azure DevOps and JIRA for project management. My collaborative approach ensures alignment with stakeholders, driving projects forward while optimizing workflows and tracking progress effectively.

Mumbai, Maharashtra, India

I have developed automated deployment pipelines using AWS CodePipeline and CodeDeploy, significantly streamlining data engineering workflows. My expertise includes monitoring and troubleshooting data pipeline performance with AWS CloudWatch and X-Ray, ensuring high availability and reliability of data processes.I designed and implemented robust ETL processes utilizing tools like Informatica and Talend Open Studio to extract, transform, and load data from diverse sources into data warehouses. Additionally, I developed error handling and recovery strategies in Matillion, enhancing the resilience of ETL operations while ensuring data accuracy and consistency.To support data-driven decision-making, I integrated Python with SQL databases for complex reporting and documentation of PySpark, Spark SQL, and Hadoop workflows. I also conducted code quality assessments using GitLab’s static analysis tools, managed JIRA issues, and ensured data integrity across Power BI reports, fostering a collaborative and high-standard work environment.

Gurgaon Rural, Haryana, India

I implemented robust data governance and security measures in Azure SQL Database, ensuring compliance and protection of sensitive information by designing and enforcing policies that maintained data integrity and confidentiality.I developed and managed ETL processes using Matillion ETL, successfully integrating data from diverse sources into cloud data warehouses. Additionally, I leveraged Azure Data Factory to connect Azure Data Lake and Azure SQL Database, creating scalable and efficient data solutions.Utilizing advanced Excel functions like VLOOKUP and PivotTables, I analyzed complex datasets to generate actionable insights. I also collaborated with cross-functional teams to create Python-based data pipelines and visualized data using Tableau, enhancing decision-making across the organization