Maharajan Thirunavukarasu
Boulder,United States
Summary
Results-driven Senior Data Engineer specializing in designing robust data pipelines and leveraging big data computing. Expertise in AWS services ensures the delivery of high-quality, scalable data solutions tailored to business needs. Proven individual contributor passionate about advancing data architectures, orchestration, quality, and governance. Consistently delivers impactful results through automation and a focus on enhancing operational efficiency.
Overview
19
19
years of professional experience
1
1
Certification
Work History
Senior Data Engineer
Amazon.com
04.2025 - Current
- Design and build data solutions in the Amazon Ads data ecosystem that influence the Advertisers business decisions.
- Develop data pipeline in Scala with Apache Spark for AWS EMR to process and deliver Apache Iceberg datasets to AWS S3.
- Review Design and Code of peers and juniors to ensure quality, and adherence to best practices.
- Collaborate with upstream and partner teams for infrastructure, data governance and privacy compliance.
Senior Data Engineer
Amazon Development Center
04.2016 - 03.2025
- Flagship Project #1: Designed and implemented Funneling process on datawarehouse that required signals from 25+ data sources for direct business impact.
- Outcome: Durable solution with sustained benefits for 3+ years for analysts and operations to resolve the blockers in the Amazon retail Selection catalog on weekly basis.
- Solution: Orchestration of dynamic deployment of transient AWS Redshift clusters and AWS DataPipeline through infrastructure as code. Orchestration of the large DAGs of tasks that contributed bit coded result datasets for end user consumption.
- Flagship Project #2: Designed and implemented Data quality validation framework at scale to detect fine grained anomalies using Z-score and other frameworks.
- Outcome: Over a period of 18 months, the solution was able to detect of data loss incidents twice for proactive resolution.
- Solution: A custom component that can be plugged into an Airflow DAG to assess granular anomalies on one or more metrics using Z-score, thereby flagging potential data loss or duplication scenarios.
Data Engineer
Amazon.com
10.2012 - 04.2016
- Flagship Project – Designed and implemented Distributed Scalable Framework on AWS using EC2, DynamoDB and S3.
- Outcome: Scalable modernization of the existing Data processing system that endured 5+ years scaling up to Billion sub-ledger events per day from upstream system and to facilitate replacement of Oracle database by AWS Redshift and S3.
- Solution: Looking back, an out-of-Box concept emulating the design principles and mental model of the current days Apache Spark. At the time of implementation of this project(2014), Spark architecture and capabilities were still in early state and evolving while Airflow did not exist.
- Built-in auto scaling on fleet of EC2 instances based on capacity.
- DynamoDB (Key Value Store) and AWS SQS(messaging) based control plane to orchestrate queuing, execution and retries.
- Load balanced multiple AWS Redshift clusters based using AWS Route 53 to scale for the user and system workloads.
Senior Project Engineer
Wipro Technologies
03.2007 - 09.2012
- Design and Develop ETL solutions on Informatica, Oracle 11g, PL/SQL.
- Operationalize and support data warehousing and OLAP solutions for high-impact reporting.
- Collaborated with cross-functional teams to deliver data solutions for retail customers onsite.
Education
Bachelor of Electronics and Communication Engineering -
ACCET
Karaikudi, India01.2004
Skills
- Programming: Python and Scala
- Open Source Frameworks: Apache Spark, Kafka, Flink, Airflow, Iceberg
- Data workflow orchestration: Apache Airflow, AWS Step function, Glue workflow
- Big Data Compute: Apache Spark, AWS Redshift
- Data modelling and optimization: DBT, AWS S3, Glue, Lake Formation
- Scripting: SQL Data Analysis, Cloud Development using Typescript and Terraform
Certification
- AWS Certified Data Engineer
The certification evaluates in-depth technical expertise to implement, monitor, troubleshoot, and optimize cost and performance for data pipelines on AWS, demonstrating a comprehensive understanding of data ingestion, transformation, security, governance, and optimal data store design.
- Databricks Certified Spark Developer
The certification evaluates a candidate's foundational knowledge of Apache Spark architecture and their ability to perform essential data manipulation tasks using the Spark DataFrame API in Python
Courses work
- Data Engineering Professional Certificate
DeepLearning.AI
- Big Data Analysis with Scala and Spark
Federal Polytechnic School of Lausanne
- Functional Programming Principles in Scala
Federal Polytechnic School of Lausanne
Timeline
Senior Data Engineer
Amazon.com
04.2025 - Current
Senior Data Engineer
Amazon Development Center
04.2016 - 03.2025
Data Engineer
Amazon.com
10.2012 - 04.2016
Senior Project Engineer
Wipro Technologies
03.2007 - 09.2012
Bachelor of Electronics and Communication Engineering -
ACCET