Sai Ratnala

About Sai Ratnala

I am a passionate and results-driven data professional with expertise in building and optimizing data pipelines, processing large datasets, and ensuring seamless data integration to enable data-driven decision-making. Proficient in big data technologies, ETL tools, and cloud platforms, with a proven ability to manage end-to-end data workflows, ensure data quality, and deliver impactful insights for critical business objectives.Skilled in leveraging AWS, Azure, and big data ecosystems like Spark, Databricks, and Hadoop to design scalable, high-performance data solutions. Adept at collaborating with cross-functional teams to implement seamless data integrations and drive continuous improvement.My academic background includes a Master of Science in Data Science, from the University of Houston. This education has equipped me with key skills in data management, cloud computing, and big data technologies, which I leverage to build efficient and scalable data pipelines. I\'ve also worked extensively with tools such as SQL, Python, and cloud platforms like AZURE, AWS, which allow me to process, transform, and store large datasets with ease.My goal is to continuously learn and apply new technologies to improve data workflows and help organizations unlock the full potential of their data.Technical Expertise Includes: • Big Data Technologies: PySpark, Spark, Databricks, Hadoop • Programming: Python, SQL, PySpark • Cloud Platforms: • AWS: S3, Redshift, Lambda, EC2, DynamoDB, RDS, Glue, Kinesis • Azure: Databricks, Datafactory, Delta Lake Storage, Synapse Analytics, SQL Database • Databases: MySQL, PostgreSQL, SQLServer, MongoDB, Snowflake • ETL Tools: Data Factory, SSIS, Apache NiFi, Informatica, Talend • Data Visualization: Tableau, Power BI, Excel Open to opportunities to tackle challenging data problems and contribute to innovative, data-first solutions.

Experience

1. Data Engineer

   PJM Interconnection

   Jan 2024 — Present · US

   Designed and implemented scalable ETL pipelines using Azure Data Factory (ADF) and Python to efficiently ingest and transform data into ADLS, enhancing data availability for cross-functional teams and supporting Power BI reporting.•Utilized Databricks, PySpark, and Python to transform large datasets, optimizing performance for batch and real-time analytics workflows, and delivering insights through Power BI dashboards.•Developed data warehousing and data lake solutions within Azure Synapse Analytics, leveraging Python-based transformations to improve storage efficiency and enabling quicker data retrieval for analysis and Power BI dashboards.•Optimized performance of PySpark and SQL queries, reducing processing times by 30% and significantly improving data processing efficiency for BI and analytics.•Built and maintained automated data pipelines with monitoring and error-handling mechanisms, ensuring consistent data flows into Power BI for real-time updates and decision-making.•Developed custom Power BI visualizations, leveraging Azure data platforms to present complex data trends and business insights in an intuitive, user-friendly format.

Education

• SRKR Engineering College

  Bachelor of Technology - BTech

  2016 — 2020

• University of Houston

  Master of Science - MS

  2022 — 2024