Regan Maharjan
@reganmaharjan
Senior Data Engineer with expertise in cloud-native data platforms.
What I'm looking for
I am a Senior Data Engineer with over 7 years of experience in designing and implementing cloud-native data platforms across various industries, including finance, insurance, healthcare, and retail. My expertise lies in building scalable ETL and streaming pipelines using AWS Glue, PySpark, and Kinesis, which have significantly improved data processing speeds and reduced operational costs.
Throughout my career, I have architected secure data lakes and integrated advanced data governance practices to ensure compliance with regulations such as HIPAA and GDPR. I have successfully migrated legacy ETL processes to serverless architectures, enhancing efficiency and reliability. My passion for data engineering drives me to continuously explore innovative solutions, such as AI-ready architectures and real-time analytics, to empower organizations with actionable insights.
Experience
Work history, roles, and key accomplishments
Senior Data Engineer
Walmart
Oct 2023 - Present (2 years)
Built scalable ETL and streaming pipelines using Python, SQL, AWS Glue, PySpark, Kinesis Data Streams, and AWS Lambda, reducing data latency across operational dashboards to under one minute. Engineered fraud detection pipelines with Kinesis, PySpark, and Python, enabling real-time flagging of anomalous e-commerce behavior. Migrated legacy Oracle and SSIS pipelines to AWS-native serverless archite
Cloud Data Engineer
State Farm Insurance
Jul 2021 - Present (4 years 3 months)
Led full migration of legacy on-prem ETL workflows to AWS Glue, Lambda, and Amazon S3 using Python and SQL, reducing average ETL runtime by 60% and eliminating infrastructure overhead. Built robust real-time streaming pipelines with Kinesis Data Firehose, Glue Streaming, and Spark Structured Streaming to process over 1 million insurance-related events per hour. Designed fraud alerting frameworks u
Data Engineer
Berkshire Hathaway
Oct 2018 - Present (7 years)
Designed and deployed a centralized data lake architecture on AWS S3, ingesting data from Oracle, mainframe, and flat-file sources across multiple subsidiaries in insurance, finance, and reinsurance. Built optimized batch and streaming ETL pipelines using AWS Glue, Redshift Spectrum, Athena, and Python (PySpark) to support regulatory reporting, internal audits, and risk analytics. Migrated 100+ le
Education
Degrees, certifications, and relevant coursework
University of Michigan
Master of Science, Computer and Information Science
Completed a Master of Science in Computer and Information Science at the University of Michigan. Focused on advanced topics in computer science and information systems.
Tech stack
Software and tools used professionally
Amazon Redshift
Apache Spark
AWS Glue
Amazon S3
AWS Step Functions
GitHub
GitLab
Kubernetes
AWS CodePipeline
Jenkins
GitHub Actions
NumPy
Pandas
PySpark
dbt
Sqoop
MySQL
PostgreSQL
MongoDB
Cassandra
Hadoop
HBase
Gmail
Node.js
Databricks
Terraform
AWS CloudFormation
Jira
styled-components
Vue.js
JavaScript
Java
JSON
XML
scikit-learn
Kafka
Prometheus
Oracle PL/SQL
AWS Lambda
Serverless
Airflow
SQL
Hugging Face
Availability
Location
Authorized to work in
Job categories
Skills
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