Surendra Babu

Extensive 20 years of IT experience with an emphasis Data Engineering, Designing, Development of Data Warehouse, Data Lake, Data Modeling, Business/Data Analysis, and Big Data Analytics. Implementation of several large-scale projects and design for the integrated business intelligence framework including Data Warehousing, Data Lake, and Analytics. Led multiple roles – Solution Architect, Data Architect, Primary Technical Lead, IT Engineer, and Operations Lead. Data warehouse Technical Lead / Data Architect with more than 15 years of experience with in-depth knowledge in Sales, Finance, Supply Chain, Subscription, service & Marketing functional domains. Successfully Migrated the legacy Datawarehouse systems to new platforms by enforcing Data modeling guidelines and Standards. Involved End to End Project Implementation which include read data from on premise, Azure DB, or Web API into Azure Blob, Azure Data Lake, and then Prepossessing it using Azure Data bricks and storing the data into Azure Data Warehouse for further processing. Experienced in gathering requirements and translate them to logic data model and physical data model with complete data profiling activities. Experience working with Data bricks notebooks & integration of the notebooks with Azure Data Factory. Working experience on python libraries, data validation. Specialties: Data modeling, Dimensional Modeling (Kimball Star, Snowflake, and Inmon ER Model) OLAP&OLTP Architecture, Data profiling, Dataflow Design, Architecture Governance and implementing cyber security standards. Enterprise Data Warehouse (EDW), Data Mart, Data Lake, and Data Engineering and Azure Cloud technologies. Work experience in all the respective database technologies like Teradata, Vertica, MSSQL, Oracle, Azure Synapse and Bigdata platforms (Hive, Presto, Scala and Spark). Processing structured, semi-structured and unstructured data. Building data pipelines with Various ETL tools and Azure SQL DW. Developed Snowflake scripts, Stored Procedures and Tasks to load data from stage (ADLS Gen2) to Snowflake raw layer. Created dedicated Snowflake Virtual warehouses for high data volumes meet critical business slas. Deigned Data sharing objects with different business partners for both snowflake and non-snowflake users. Developed Snowflake external tables for Business to explore the data. Developed snowflake UDTFs to reuse common logic across multiple queries. Assisted the data scientists with building features and deploy them into production using snowflake ML and governed the models using snowflake registry. Generated GENAI and large language models (LLM) apps using snowflake Cortex. Designed and developed snowflake data masking polices for sensitive data. Have experience in creating pipeline jobs, schedule triggers using Azure data factory (ADF). Excellent verbal, written communication skills; ability to interact professionally with diverse groups including executives, managers, and subject matter experts and adapts to modern technologies, circumstances, and environments. Background includes data mining, warehousing and analytics. Proficient in machine and deep learning. Quality-driven and hardworking with excellent communication and project management skills. Respected [Data Architect] with history of creating system architectures that reduce costs and streamline operations. Ready to create design plans from whole cloth or tackle revamps of disparate networks full of outdated systems. Uses emerging and nascent technologies to create stress-free operations both on site and via remote locations and online.

Azure Data Engineer