Shruti Tellur

About Shruti Tellur

Possess over 6 years of experience in data engineering field, focusing on the creation and enhancement of efficient data solutions that cater to various sectors such as Banking, Energy Infrastructure, Telecommunication, Health Care, Information Technology * Currently overseeing the design and execution of complex data pipelines, utilizing advanced cloud technologies to guarantee optimal data quality and performance while driving innovative solutions.* Developed a profound understanding of data engineering roles, encompassing data ingestion, transformation, and warehousing, while honing skills in tools such as Azure Data Factory, Apache Spark, and SQL. Exhibit strong leadership & communication capabilities, promoting teamwork across diverse groups to synchronize data strategies with organizational goals and improve decision-making effectiveness.* Proficiency in dimensional modeling & best practices in data warehousing, guaranteeing that data architectures are crafted for superior performance. Proficient in leveraging advanced data engineering techniques, including ETL process optimization and cloud architecture design, to deliver scalable and efficient data solutions that drive business intelligence and analytics. Established a robust framework for data governance and compliance, ensuring that all data management practices not only meet but exceed industry standards, thereby enhancing organizational trust in data integrity.

Experience

1. Data Engineer Sr Analyst

   Accenture

   Apr 2021 — Present · Bengaluru, IN

   Partnered with data ingestion team to architect and deploy data pipelines using Azure Data Factory (ADF), ensuring efficient extraction andloading of data into Azure Data Lake Storage (ADLS).• Managed the full lifecycle of data ingestion, ensuring data quality and consistency. Leveraged PySpark to cleanse and process raw data, storing itin the transform container within ADLS for further refinement and analysis.• Optimized Apache Spark jobs by fine-tuning Spark configurations, enhancing distributed data processing efficiency.• Extracted domain details from Databricks notebooks, transformed the data into a tabular format, and loaded it into Azure Data Lake Storage(ADLS).• Retrieved necessary information from both serverless and dedicated Synapse environments and loaded the finalized data into lineage tables• Developed and automated data reconciliation processes using ADF pipelines and PySpark to validate data consistency between source and targetdatasets.• Led efforts in data warehousing, developing dimension, fact, and lookup tables that supported efficient and effective reporting and analysis.• Automated error reporting and handling mechanisms, reducing manual intervention and significantly improving data quality control processes.• Utilized advanced performance techniques such as partitioning, caching & query optimization to minimize processing time & improveperformance of large-scale data transformations.

Education

• International Institute of Information Technology Bangalore

  Master's degree

  2025

• Walchand Institute of Technology, Solapur

  Bachelor's degree

  2014 — 2017