Data Warehouse Engineer - Azure & AWS Expert

Gunakar Dornala

Plano, TX +1-913-***-**** ***********@*****.***

PROFESSIONAL SUMMARY

Data Warehouse Engineer with 5+ years of experience designing and optimizing data warehousing solutions and ETL processes across Linux-based Azure and AWS environments. Strong background in shell scripting, Oracle (including Exadata), and relational database development, with practical Python and Perl experience, Agile delivery, and a focus on automation and continual process improvement. CORE SKILLS

• Azure: Azure Data Factory (ADF), Azure Databricks, ADLS Gen2, Synapse Analytics, Event Hubs, Azure Functions, AKS, Azure DevOps, Key Vault, Azure Monitor

• AWS: AWS Glue, Amazon S3, EMR (Spark), Redshift, Lambda, Kinesis, RDS, DynamoDB, Athena, EKS, IAM, CloudWatch

• Data Engineering: Apache Spark, PySpark, Spark SQL, Kafka, Hadoop (Hive, Sqoop), Delta Lake, Data Warehousing, ETL Tools, Informatica, Airflow, Python, Perl

• Databases: Synapse, Redshift, PostgreSQL, SQL Server, Oracle, Snowflake, Oracle Exadata

• Orchestration & CI/CD: Azure DevOps, Glue Workflows, Step Functions, Jenkins, Git, GitHub Actions, Agile Methodology

• Containers & DevOps: Docker, Kubernetes (AKS & EKS), Terraform, Shell Scripting, Linux Environment Setup, Unix File Systems

• BI & Reporting: Power BI, Tableau

• Data Governance: Data Validation, Reconciliation, Schema Evolution, RBAC/IAM, Encryption, Audit Controls PROFESSIONAL EXPERIENCE

Capitol Federal Savings Bank Jul 2025 - Present

Data Warehouse Engineer USA

• Designed end-to-end ETL/ELT pipelines using Azure Data Factory, ADLS Gen2, and Azure Databricks for mortgage and loan datasets, enabling faster data availability for downstream analytics

• Built scalable PySpark workflows in Azure Databricks that transformed financial data for credit risk and regulatory analytics, reducing data preparation time

• Developed optimized Synapse warehouse models improving query performance and reporting efficiency.

• Implemented streaming ingestion using Event Hubs and Spark Structured Streaming for near real-time loan event processing.

• Automated orchestration and monitoring of data pipelines using shell scripting, Azure Data Factory and Azure Monitor, improving operational reliability and reducing manual oversight

• Enforced RBAC policies, Key Vault encryption, and audit logging to meet compliance requirements.

• Deployed containerized services using Docker and AKS, enabling scalable data microservices that support increased processing capacity and improve system reliability

• Optimized Spark workloads and Synapse queries to reduce latency and improve dashboard refresh cycles. National Insurance Company (Cognizant) May 2022 - Jul 2023 Data Warehouse Engineer India

• Designed and implemented ETL/ELT pipelines with AWS Glue, S3, EMR (PySpark), and Redshift to load insurance claims and policy data, which streamlined data availability for downstream analysis

• Built fact and dimension tables in Redshift for actuarial, underwriting, and regulatory reporting, creating a unified data model that reduced report generation time by 30%.

• Implemented event-driven streaming architecture using Amazon Kinesis to feed near real-time fraud detection workflows, allowing quicker identification of suspicious activity

• Automated workflow orchestration with Glue Workflows and AWS Step Functions, reducing manual scheduling effort and improving pipeline reliability

• Enforced IAM policies, applied KMS encryption, and set up CloudWatch monitoring to secure data access and track usage, supporting audit compliance

• Optimized Spark transformations and Redshift queries for performance and cost efficiency. Baxter International Inc Jun 2020 - Apr 2022

Data Warehouse Engineer India

• Designed and implemented an enterprise data lake using ADLS Gen2, Azure Data Factory, and Azure Databricks, enabling secure storage of clinical data and reducing data onboarding time by 40%.

• Built scalable ETL pipelines in Python and Spark following Agile methodology to ingest and transform clinical and device telemetry datasets, increasing data availability and speeding up analyst access by 40%.

• Developed data warehousing dimensional models in Azure Synapse using SQL, which improved accuracy and reduced reporting time for healthcare analytics across the enterprise.

• Implemented batch and streaming data ingestion with Event Hubs and Spark, improving data processing speed and reliability for downstream analytics.

• Integrated Power BI with Synapse to build automated executive dashboards, reducing reporting time by 40% and giving leadership faster access to key business insights.

• Migrated legacy Hadoop workloads to Azure using Azure Data Factory and Terraform, moving data to Amazon S3 and Redshift, which improved data processing speed by 30% and reduced storage costs by 20%.

• Implemented data quality validation, monitoring, and governance controls using Step Functions and Terraform, adding encryption and audit features that improved data reliability by 30% and ensured full regulatory compliance. Walmart (Infosys Ltd) Nov 2018 - May 2020

Data Warehouse Engineer India

• Built distributed Spark pipelines on AWS Glue Workflows using IAM roles to process clickstream, POS, and inventory data, delivering near-real-time data availability for downstream analytics

• Developed and implemented warehouse-ready datasets by transforming raw Oracle Exadata data and storing results in Amazon S3, which improved data accessibility for business users and enabled more accurate pricing optimization and inventory analytics.

• Optimized large-scale SQL transformations on Amazon Redshift/EKS, cutting query runtimes and lowering compute costs for analytical workloads

• Automated ETL orchestration and dependency management on Unix file systems using Airflow, integrating CloudWatch monitoring and Key Vault secrets, which reduced manual scheduling errors by 90% and improved data pipeline reliability.

• Implemented data validation and reconciliation frameworks across retail datasets using custom Spark checks and IAM policies, ensuring data quality and reducing downstream issues CERTIFICATIONS

• Microsoft Azure Fundamentals (AZ-900)

• Microsoft Fabric Data Engineer Associate (DP-700)

• AWS Certified Data Engineer – Associate (Pursuing) EDUCATION

University of Central Missouri 2023 - 2025

Master’s, Big Data Analytics & Information Technology Osmania University 2013 - 2017

Bachelor’s, Mechanical Engineering

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