Nithin Sankar Bahunadam

• Senior Data Engineer / Data Analyst with 7+ years of experience in designing, developing, and optimizing large-scale data pipelines, ETL workflows, and analytics solutions using cloud platforms Such as Azure and AWS.
• Expertise in migrating SQL databases to Azure Data Lake, Azure Synapse Analytics, and Databricks, ensuring high availability, optimized performance, and cost efficiency.
• Skilled in cloud security and access management, configuring AWS IAM, Snowflake RBAC, and Azure role-based access controls to ensure compliance and data governance.
• Developed and optimized real-time analytics solutions using Azure Stream Analytics and AWS Lambda, integrating with event-driven architectures for rapid data processing.
• Hands-on experience in building scalable serverless solutions using Azure SQL pools in Synapse Analytics, improving data processing efficiency and reducing infrastructure costs.
• Expertise in designing and deploying AWS-based data solutions, integrating Redshift, RDS, and DynamoDB to support large-scale analytics and business intelligence needs.
• Proficient in ETL development using Azure Data Factory, AWS Glue, and Informatica PowerCenter, enabling seamless data transformation and ingestion across cloud and on-premises environments.
• Proficient in statistical analysis using Python (Pandas, NumPy), R, and SAS, applying regression, clustering, and hypothesis testing for deep data insights.
• Skilled in real-time data streaming using Kafka, Spark Streaming, and Apache Flume, ensuring low-latency ingestion and processing for high-velocity data pipelines.
• Experienced in developing and tuning PySpark applications, leveraging MLlib for predictive analytics, clustering, and real-time business intelligence.
• Strong experience in big data processing using Hadoop, Spark, PySpark, and MapReduce, optimizing distributed computing workflows for efficient large-scale data transformation.
• Proficient in NoSQL databases such as Cassandra, MongoDB, and HBase, designing scalable architectures and implementing distributed database solutions for high-performance applications.
• Hands-on expertise in SQL, PostgreSQL, MySQL, and Snowflake, optimizing query performance, indexing, partitioning, and materialized views to enhance analytical efficiency.
• Expertise in optimizing SQL queries, stored procedures, and triggers in Oracle, MySQL, and PL/SQL, reducing execution time and improving database performance.
• Skilled in Google Analytics and A/B testing strategies, leveraging data-driven insights to optimize marketing campaigns, customer engagement, and business growth.
• Expertise in orchestrating workflows using Apache Airflow, developing custom DAGs and operators to automate end-to-end data pipelines and ETL jobs.
• Strong ability to develop advanced Power BI dashboards and Tableau visualizations, leveraging complex DAX calculations and interactive reports for actionable business insights.
• Experience in automating report refresh schedules in Power BI and Tableau, integrating with cloud data sources for real-time analytics.
• Strong background in data modeling and pipeline optimization, implementing best practices in data warehouse design and schema optimization for high-performance querying.
• Experienced in configuring and optimizing Jira and GitHub workflows, ensuring seamless collaboration and CI/CD integration across data engineering teams.

Senior Data Engineer and Analyst with 7+ years of experience delivering scalable data platforms and analytics solutions across cloud (Azure, AWS), big data, and BI ecosystems. Proven track record in designing and optimizing ETL/ELT pipelines using Azure Data Factory, Informatica, AWS Glue, and Apache Spark. Skilled in building real-time and batch data processing workflows with Kafka, Flume, and Spark Streaming, supporting high-volume ingestion and advanced analytics.

Expert in data modeling, warehouse development (Redshift, Snowflake, Synapse), and visualization using Power BI and Tableau. Hands-on experience in implementing predictive models and clustering techniques using PySpark MLlib, SAS, and Python to support data-driven decision-making. Adept at leveraging CI/CD practices with Git, Airflow, and Azure DevOps for workflow orchestration and monitoring.

Worked across diverse industries—healthcare, insurance, pharma, retail—and contributed to data modernization, cloud migration, and cost optimization initiatives. Demonstrated ability to collaborate with cross-functional teams, improve data reliability, and deliver business-impactful insights through enterprise-scale reporting solutions.

• Masters in Bigdata Analytics and Information Technology (May 2023 – Dec 2024) University of Central Missouri, Warrensburg, MO
• BTech in Computer Science and Engineering (June 2014 - May 2018) GITAM University, Visakhapatnam, India