Anurag Wasnik

About Anurag Wasnik

Data Engineer with 7+ years of overall industry experience working across the different stages of pipeline including ingestion, data cleaning, enriching and transforming data etc. with the help of big data technologies. Expertise in Spark development for building data intensive applications.Skills:• Understanding of Agile Software Delivery and planning techniques.• Languages: Python for Data Science• Big Data Tools: SparkSQL, Spark/PySpark• Database: SQL - Proficient in Tables, Views, Procedures, Nested Queries, Joins and extracting data from databases using MySQL.• Cloud: AWS S3, Glue Studio, Lambda, Step Function, Athena, DynamoDB, RDS Aurora, RedShift, QuickSight, OpenSearch.• Machine Learning: Well-acquainted with Supervised Learning (Regression and Classification), Unsupervised Learning Techniques (Clustering, Association, PCA), Time Series Analysis, Ensemble Techniques Stacking, Bagging, Boosting).• Data Analytics Tool: Power BI, Tableau - Well versed with the creation of various visualizations, developing effective, dashboards and stories to convey meaningful insights.• Data Visualization: Matplotlib, Seaborn, Tableau, Plotly.

Experience

1. AVP - Data Engineer

   NatWest Group

   Jul 2025 — Present · Gurugram, IN

   Designed and implemented a scheduled ETL pipeline using AWS Glue, PySpark and Glue Triggers to process Amazon Connect data, performing data cleaning and transformation, and converting json to partitioned parquet for optimized storage in s3. Enabled real-time data streaming by integrating Confluent Cloud Kafka with AWS Lambda over secure VPC connectivity, supporting scalable, serverless event-driven banking use cases. Integrated AWS-based Spark and Glue pipelines with Snowflake to publish analytics-ready datasets for reporting teams. Developed visually compelling QuickSight reports by integrating processed data from Athena SQL queries and improving query performance. Implemented and configured cross-region replication for S3 buckets, facilitating real time data sharing with the Data Analytic team. Utilized Python along with S3 Batch operations to replicate existing data, incorporating robust error handling mechanisms to efficiently address and resolve failed object replication. Automated the entire S3 Batch operations process using AWS Lambda functions, DynamoDB, and event notification. Utilized Terraform in conjunction with GitLab to automate the deployment of resources within AWS environments.

Education

• Dr.Babasaheb Ambedkar College of Engineering and Research

  Bachelor of Engineering - BE, Electronics and Communications Engineering

  2012 — 2016

• Great Learning

  Post Graduation Program in Data Science and Engineering, Data Science

  2020 — 2021