Data Engineer

Madhupal Singu Data Engineer

*************.****@*****.*** +1-513-***-**** LinkedIn

Summary

Multi-cloud Data Engineer with 5+ years of experience designing and optimizing large-scale data ecosystems across AWS, Azure, and GCP. Proven expertise in building cloud-native data lakes, enterprise data warehouses, and real-time streaming pipelines for healthcare and finance domains. Skilled in Python, SQL, and Spark with deep hands-on experience in AWS for U.S. healthcare systems and Azure + Snowflake + GCP for India-based financial platforms. Adept at improving query speed, cost efficiency, and compliance (HIPAA, GDPR, SOX) while enabling predictive analytics and AI/ML-driven insights. Recognized for delivering secure, scalable, and business-aligned data solutions that accelerate decision-making.

Technical Skills

• Languages & Scripting: Python (Pandas, PySpark), SQL, Scala, Java, Bash

• ETL & Orchestration: Apache Airflow, dbt, Apache NiFi, Azure Data Factory, AWS Glue

• Big Data & Streaming: Apache Spark (batch & streaming), Hadoop (HDFS, Hive, HBase), Kafka, Flink

• Cloud Platforms: AWS (S3, Glue, Redshift, Lambda) Azure (Data Factory, Synapse, Data Lake, Functions) GCP (BigQuery, Dataflow, Pub/Sub, Composer)

• Warehousing & Storage: Snowflake, Redshift, PostgreSQL, MySQL, MongoDB, Cassandra, Dimensional Modeling

• Infrastructure & DevOps: Docker, Kubernetes, Git, Terraform (IaC), CI/CD pipelines, DataOps practices

• Governance & Security: Data quality frameworks, monitoring, encryption, HIPAA/GDPR/SOX compliance

• Analytics & BI: Power BI, Tableau, ML/AI pipeline integration, real-time dashboards Professional Experience

Data Engineer, Cigna Apr 2024 – Present USA

• Engineered HIPAA-compliant ETL pipelines in AWS Glue that process over 2 TB of claims and EHR data daily, embedding encryption, auditing, and granular access controls that safeguard sensitive patient records.

• Optimized AWS Redshift data warehouses through schema redesign, distribution key tuning, and partitioning, resulting in a 30% improvement in query response times for large healthcare analytics workloads.

• Automated real-time ingestion pipelines with AWS Kafka + Spark, reducing latency by 45% and enabling hospital administrators to monitor operational dashboards with near-instant updates.

• Developed a Python-based anomaly detection and monitoring framework leveraging AWS CloudWatch and custom alerting rules, achieving 99.8% data accuracy and preventing compliance reporting errors.

• Migrated 150+ legacy SQL Server ETL jobs into AWS Redshift with Dockerized workflows, using CI/CD pipelines in Git to cut operational costs by 20% and shorten release cycles.

• Partnered with compliance, analytics, and data governance teams to deliver AWS S3-based data lakes and Redshift marts, streamlining HIPAA reporting and reducing regulatory submission time by 25%.

• Integrated legacy on-premise datasets from HDFS/Hive into AWS-native pipelines, enabling predictive healthcare analytics, patient risk scoring, and data-driven outcome optimization across multiple hospitals. Data Engineer, Neon IT Systems Nov 2019 – July 2023 India

• Designed and deployed Azure Data Factory pipelines to orchestrate complex ETL workloads, moving massive volumes of financial, market, and compliance data into Snowflake warehouses with high availability.

• Built a hybrid GCP BigQuery + Snowflake platform that stored structured and semi-structured datasets, powering sophisticated fraud detection models and near real-time portfolio risk monitoring for traders.

• Automated financial reconciliation workflows with PySpark and Azure Synapse, improving transparency in audits and reducing discrepancies by 35% across multiple financial reporting systems.

• Tuned Snowflake clusters and ETL performance through caching, clustering, and compression, cutting runtimes by 50% and enabling faster time-to-insight for portfolio managers.

• Implemented GCP Pub/Sub + Dataflow pipelines to capture and process trade events in real time, enhancing proactive fraud detection and ensuring resilient financial risk monitoring.

• Collaborated with compliance, governance, and trading stakeholders to establish SOX-compliant data marts on Snowflake, ensuring audit readiness and improving reporting reliability across financial domains. Education

Master of Science, Information Technology,University of Cincinnati, Cincinnati, OH Aug 2023 – Dec 2024 Bachelor of Technology in computer science, veltech university, chennai May 2018 – May 2022 CERTIFICATIONS

• AWS Fundamentals: Going Cloud-Native” Certificate from Coursera

• Microsoft Certified: Power BI Data Analyst Associate (PL-300)

• Coursera – Data Engineering on Google Cloud

Contact this candidate