Headline

Data Platform @ CRED | Building Data Solutions | Ex- Angel One ,PayU

About

# About Me – Lead Data Engineer | 9+ Years in FinTech & Data Engineering ➔ I specialise in architecting and scaling cloud-native data platforms tailored for modern financial workloads. With over a decade of experience, I bring deep expertise across big data ecosystems, data modelling, orchestration, and real-time data processing. # What I Do: ➔ Currently leading the data platform initiatives at CRED , helping them scale there platform to PetaByte Scale in a cost efficient way . ➔ Extensive hands-on experience in Big Data Engineering, Data Warehousing, and cloud-native data architecture. ➔ Expertise in data modelling, data platform and lake design, and orchestration at scale. ➔ Proficient in building and optimising ETL pipelines using Python, Apache Spark, and Kafka. ➔ Deep knowledge of the Hadoop ecosystem including Spark, MapReduce, HDFS, and Sqoop. ➔ Experience in implementing data warehouses using Amazon Redshift and data lakes using Amazon S3 and Amazon Spectrum. ➔ Built robust data pipeline orchestration frameworks using Apache Airflow. ➔ Strong SQL background with experience in MySQL, Postgres, and Redshift. ➔ Worked extensively with NoSQL databases like MongoDB and Cassandra, and graph databases like Neo4j and OrientDB. ➔ Built business intelligence dashboards and reports using Tableau for executive and operational decision-making. ➔ Hands-on experience in containerising services using Docker and deploying scalable applications. ➔ Proficient in object-oriented programming with Java and Spring Framework. ➔ Deep domain knowledge in FinTech, stock investments, and credit risk modeling. # Leadership & Delivery: ➔ Experienced in managing data engineering teams, mentoring colleagues, and driving technical best practices across squads. ➔ Comfortable rolling up my sleeves to solve burning issues, ship faster, and contribute as an individual contributor . ➔ Proven ability to handle petabyte-scale data systems with low-latency processing requirements in production environments. # My Aspiration: ➔ To lead the development of scalable, secure, and efficient data platforms that empower businesses to become truly data-driven, while nurturing strong technical teams that deliver with excellence.

Location

Bengaluru

AI stack

antigravity

codex

Work experience

Lead - Data Platform at CRED, Oct 2025 - Present · 11 mos, Bengaluru

Lead Data Engineer at Angel One, Apr 2024 - Oct 2025 · 1 yr 7 mos, Hybrid, Redefined Clickstream Data Platform & Analytics at Angel One The platforms capture’s upto 10 billion events , 2 TB data in real time on daily basis . This includes multiple processing layers which are totally synchronous which captures and process this data to cater multiple Analytics use case like Behavioural Analytics , Customer 360 , User Journey Funnel etc

Senior Data Engineer at Angel One, Nov 2021 - Apr 2024 · 2 yrs 6 mos, Bengaluru, Karnataka, India, Built Unified Data Platform for Angel One. Ingestion Layer - • Built self serve data ingestion framework to bring raw data across 200 + individual data sources to centralised data lake. • The ingestion layers serves 2000 + data pipelines , processing ~4 TB of data on daily basis • Data Sources Supported - Mysql , MsSQL , Postgres, S3 & DynamoDB • Tech Stack Used - Pyspark , EMR , Airflow , Python ,S3 & Delta Lake Transformation Layer - • Utilised the diverse raw data & transformed it to meaningful metrices & aggregates • Transformation layer generates 10000 + attrbutes which serves more than 100 + BI reports • 50 + transformation pipelines utilises generic transformational framework to remove redundancy in code & data • Optimised spark jobs for optimum Resource utilisation & handling failover mechanism by implementing proper alerting & monitoring stacks. Data Warehousing Layer - • Built & managed the entire data warehouse ecosystem using AWS Redshift • Implemented adequate distribution & indexing of data for faster query execution • Transformed redundant queries to materialised views to reduce load on cluster • Implemented Optimised Concurrency scaling of the cluster to handle load during peak market hours & save cluster cost at the same time • Handled peak load of 7 lakh queries a day (Complex BI reporting queries for Angel One Partner platform) Data Catalog - • Researched & Built the Data Cataloging layer from scratch. • Provided features like Data Discovery , meta data Management, Data Lineage & Data Governance • Utilised OpenMetaData Cataloging tool & deployed it Kubernetes(AWS EKS) • Onboarded 30K + Tables on data catalog & Provided data lineage mapping for all critical BI reports data flow end to end

Senior Data Engineer at PayU, Apr 2020 - Nov 2021 · 1 yr 8 mos, Bengaluru, Karnataka, India, Built the Next-Generation Data Platform for PayU • Created the Central Data Lake using Apache Hudi as a Data Lake Management Framework, for ingesting Batch as well streaming data. -> The Data Lake comprises of two data zones - Raw Data Zone & Feature Zone. The raw zone is our central source of truth for all of our downstream systems, feature zone is the aggregated layer built on top of the raw zone, which stores the features of the Data Science & Analytics Models. • Designed & Developed the Central Data Cataloging & Data Discovery Tool -> With increasing more data sources & more attributes being added to the system, to manage them efficiently we developed a data cataloging framework to feed all the metadata related to all the attributes we have in our platform. Data Discovery tool uses MetaData for searching the data attributes, features available in our platform for the Product Managers, Data Analysts & Data Scientists for their day-to-day work. • Feature Store for ML Platform - -> Designed & Built the consolidated feature store as part of our ML Data Platform for storage & retrieval of features of various Data Science & Analytical Models.

Data Engineer at PayU, Apr 2019 - Mar 2020 · 1 yr, Bengaluru Area, India, • Primarily involved in Design and Architecture of Big Data Platform at PayU. • The Data Platform has been built upon AWS Redshift, S3, DMS, Kinesis, Athena,EMR. • Accurately implemented Big Data technologies - Hadoop, HDFS, Apache Spark, Cassandra . • Built Batch Processing pipelines, ETL ,Data Lake, Data Warehousing • Accurately implemented Orchestration layer of Data Pipelines using Apache Airflow • Involved in setting up the infra, orchestration, monitoring, and alerting stack.

Software Engineer - Data Science at PayU, Jul 2017 - Mar 2019 · 1 yr 9 mos, Bangalore,Karnataka India, Worked on various Data Products at PayU solving problems like Risk , Rewards , Credit & Fraud Detection Technologies used - | PYTHON |JAVA | Spring Framework | AWS | Credit Risk Analysis | SQL | Graph-DB | Neo4j | MongoDB| REST SERVICES | MIS - Reporting

Education

Bachelor of Technology (BTech), Computer Science, Shri Ram Murti Smarak (SRMS) Institutions

Nanodegree Program, Data Engineering, Udacity