Sreejanya Gonti

E-Commerce, USA| TechStack: Snowflake, Github, DBT, Tableau| Team Size: 4

• Refactor and migrate SQL scripts to DBT cloud models.
• Assist with system architecture for the new DBT cloud system.
• Perform all the other data engineering duties in Airflow, Snowflake, Python as instructed by the Sr. Manager of Analytics Engineering.
• Enhance the existing models to meet business requirements.
• Implement new procedures and incorporate new functionalities into existing system
• Monitor data pipelines ensuring successful report deliveries.
• Update and create Tableau dashboards.

E-Commerce, USA| TechStack: Python, Airflow, Snowflake, Git, DBT| Team Size: 5

• Led the migration of data from a consolidated database to brand-specific databases, ensuring a seamless transition in Snowflake.
• Automated the validation process using Python to validate the integrity and accuracy of the migrated data.
• Designed robust, reusable and scalable data driven solutions and data pipeline frameworks to automate the ingestion, processing and delivery of both structured and semi structured data.
• Designed data pipelines using Python to load data from heterogeneous source systems like databases, file systems and APIs.
• Used multiple python data structures to extract, transform and load data from different social media APIs to Snowflake.
• Created custom script to fetch the data to AWS S3 buckets from different API endpoints in JSON format using Python
• Took charge of optimizing existing Snowflake SQL scripts, fine-tuning queries for improved performance.
• Implemented best practices to enhance data processing efficiency within the Snowflake environment.
• Resolved incoming data analytics issues promptly, demonstrating agility and problem-solving skills.
• Addressed ad-hoc requests from data analysts, providing quick and effective solutions within the Snowflake and Python environment.
• Implemented alert systems to notify developers of discrepancies and failures in the Snowflake transformation scripts.
• Proactively identified and addressed issues, ensuring data quality and minimizing downtime.
• Enhanced Snowflake SQL scripts to accommodate business changes and fulfill analyst requirements, ensuring flexibility and adaptability.
• Collaborated with analysts to understand evolving business needs and adjusted scripts accordingly.
• Provided crucial support to the production environment by actively monitoring Airflow Directed Acyclic Graphs (DAGs).
• Made essential modifications to DAGs, seamlessly incorporating necessary tasks to enhance and extend data pipeline functionalities
• Collaborated with team members, utilizing Git to maintain a well-organized and documented codebase.
• Ensured the smooth flow of data by addressing issues promptly and maintaining the reliability of data pipelines.
• Conducted regular checks and optimizations, contributing to the overall reliability of data orchestration.
• Engaged in continuous learning and exploration of DBT capabilities to maximize its potential in the data transformation process.
• Currently spearheading the migration of SQL scripts to DBT (Data Build Tool) models.

BI Solution for leading Healthcare Client, USA|TechStack: Azure Databricks, Azure Data Factory, Azure Data Lake, Azure SQL, Pyspark|Team Size: 7

• Implemented a BI solution in Azure that provided essential data and metrics to a rating application, enabling customers to track and monitor their progress effectively.
• Led the analysis of business requirements, translating them into Pyspark solutions to efficiently acquire and process metrics.
• Collaborated closely with stakeholders to understand and align technical solutions with business goals.
• Orchestrated the ingestion of data from FileShare to Azure Data Lake, employing Azure Data Factory for efficient and scalable data movement.
• Ensured a reliable and secure transfer of data, adhering to industry best practices.
• Utilized Pyspark in Azure Databricks to extract data from diverse sources, including fixed-width text files and CSV files.
• Applied expertise in handling varied data formats, ensuring comprehensive data acquisition.
• Implemented data transformation processes to convert ingested data into enriched parquet files.
• Optimized resource usage by structuring data in parquet format, enhancing performance and facilitating analytical queries.
• Loaded enriched data seamlessly into Azure SQL, ensuring data availability for the frontend application.
• Ensured seamless integration with the frontend application for a user-friendly experience.
• Maintained data integrity and consistency during the loading process.
• Applied Machine Learning (ML) algorithms using SciKit-Learn python module on enriched data to generate predictive insights.
• Conducted thorough Unit, Integration, and Regression testing in both development and production environments.
• Ensured the reliability and accuracy of the BI solution, addressing potential issues proactively.
• Collaborated effectively within a team of 7 professionals, ensuring streamlined communication and efficient project delivery.
• Contributed to a collaborative work environment, sharing knowledge and expertise to meet project goals.

Financial Services Corporation|TechStack: DataStage, Matillion, Snowflake, Attunity| Team Size: 10

• Orchestrated the migration of a substantial Oracle DataWarehouse to Snowflake Data Warehouse, ensuring a seamless transition.
• Navigated the complexities of transferring data between different database systems, demonstrating expertise in migration strategies.
• Acquired data from various sources, including Oracle tables and S3, showcasing versatility in handling data from heterogeneous environments.
• Demonstrated proficiency in extracting, transforming, and loading data from disparate sources into a unified Snowflake Data Warehouse.
• Migrated DataStage jobs to Matillion, leveraging Matillion ETL for enhanced data transformation capabilities.
• Loaded DataWarehousing tables into Snowflake, utilizing Matillion's intuitive and powerful ETL functionalities.
• Orchestrated Matillion jobs to acquire data from S3 files, optimizing data processing workflows.
• Implemented efficient scheduling and coordination of tasks to streamline the data orchestration process.
• Created robust pipelines for shared jobs, emphasizing reusability and scalability in the data processing framework.
• Engineered Matillion CDC jobs and transformation jobs, enhancing the adaptability of the solution to changing business requirements.
• Conducted comprehensive unit testing of Matillion jobs, ensuring the reliability and accuracy of the data processing workflows.
• Implemented automated Snowflake stored procedures for systematic and repeatable testing procedures, contributing to quality assurance.
• Applied optimization techniques while loading DataWarehousing tables into Snowflake, maximizing performance and efficiency.
• Leveraged Snowflake-specific features to enhance data storage and retrieval speed.
• Ensured comprehensive documentation of the migration process, facilitating knowledge transfer within the team.
• Contributed to a knowledge-sharing culture, empowering team members to navigate and troubleshoot the implemented solution.