Sai Satvikh Lakkimsetty

About Sai Satvikh Lakkimsetty

Senior Data Engineer with 10+ years of experience designing and building scalable data platforms, high-performance ETL/ELT pipelines, and real-time streaming architectures across AWS, Azure, and Google Cloud.Specialized in processing large-scale distributed datasets using Apache Spark, Databricks, Kafka, and modern cloud data warehouses including Snowflake, Redshift, BigQuery, and Azure Synapse. Experienced in building reliable data pipelines and modern data lake architectures that power enterprise analytics, machine learning, and real-time business intelligence.Throughout my career, I have designed and implemented distributed data processing systems capable of handling high-volume data across healthcare, networking, insurance, payroll, and logistics industries. My focus is on building scalable, reliable, and cost-efficient data infrastructure that enables organizations to transform raw data into actionable insights.Key expertise includes:• Big Data Processing: Apache Spark, PySpark, Spark SQL, Databricks• Streaming Data Platforms: Apache Kafka, Spark Structured Streaming, Flink, Kinesis, Event Hubs• Cloud Data Platforms: AWS, Microsoft Azure, Google Cloud Platform• Data Warehousing: Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse Analytics• Workflow Orchestration: Apache Airflow, Azure Data Factory• Programming: Python, SQL• Data Architecture: Data Lakes, ETL/ELT Pipelines, Distributed Data SystemsI enjoy solving complex data engineering challenges and building modern data platforms that enable scalable analytics, real-time insights, and data-driven decision making.Open to connecting with data professionals, engineering leaders, and organizations building modern data platforms.

Experience

1. Senior Big Data Engineer

   Walgreens

   Jun 2024 — Present · Deerfield, IL, US

   At Walgreens, I design and build scalable data platforms that process large volumes of healthcare and pharmacy data in batch and real-time environments. I develop enterprise ETL pipelines using Apache Spark, Databricks, and AWS to process HL7 and FHIR datasets, ensuring HIPAA compliance while enabling actionable insights for analytics teams.I build real-time streaming pipelines with Apache Kafka, AWS Kinesis, and Apache Flink to support operational decision-making and sub-second analytics for patient and pharmacy operations. I implement data quality frameworks using Great Expectations and Deequ, integrated into Apache Airflow and Dagster workflows, and maintain governance and metadata catalogs with Collibra and DataHub.I optimize Spark workloads on Databricks to reduce ETL job execution times by up to 60%, design and maintain AWS Lake Formation data lakes and Snowflake warehouses, and manage CI/CD pipelines using Jenkins and Argo Workflows for automated, repeatable deployments.

Education

• Tirumala junior college

  Intermediate, Marks:974

  2018 — 2020