Senior Data Engineer Cloud, ETL/ELT, Lakehouse Architect

Naveen kukudala

Email: ****************@*****.***

Mobile: 732-***-****

LinkedIn: www.linkedin.com/in/naveen-kukudala-8a5568323 Data Engineer

PROFESSIONAL SUMMARY

Architected 5+ years of data engineering solutions across Azure, AWS, and GCP, delivering scalable pipelines, governed platforms, resilient integrations, and analytics-ready enterprise datasets consistently.

Specialized in ETL/ELT, data modeling, lakehouse architecture, orchestration, and cloud migration with Python, SQL, Spark, Databricks, Airflow, dbt, and modern warehousing platforms for analytics.

Strengthened data quality, lineage, observability, governance, and security controls while enabling reporting, self- service analytics, trusted integrations, and reliable downstream data consumption across regulated environments.

Collaborated with cross-functional teams to automate ingestion, optimize performance, and deliver trusted data products supporting analytics, governance, operational reporting, compliance, and decision-making at scale.

Demonstrated leadership skills by inspiring teams to exceed project goals, resulting in a 30% productivity increase.

Mentored development teams to enhance coding practices, leading to a 25% reduction in project errors.

Mentor guide teams to foster collaboration and innovation, significantly improving project delivery timelines. TECHNICAL SKILLS

Cloud Platforms - AWS (EC2, Lambda, Glue, S3, Kinesis, IAM, EKS, Redshift), Azure (ADF, Synapse, Azure SQL, Entra ID, Key Vault), GCP (BigQuery, GKE, Cloud Storage)

Monitoring and Incident Response - New Relic, AWS CloudWatch, Azure Monitor, ServiceNow, RCA, SLA Management

Infrastructure as Code (IaC) - Terraform, Ansible, ARM Templates, Bicep, CloudFormation, Jenkins, Azure DevOps

CI/CD and DevOps - Jenkins, GitHub Actions, Git, GitLab, CodePipeline, CI/CD Pipelines, Shell Scripting Programming & Scripting - Python, SQL, Bash, PowerShell, CI/CD automation pipeline management

Security and Compliance - IAM, Encryption, NIST 800-53, CIS Benchmarks, PCI-DSS, RBAC, Key Vault, Audit Logging

Databases - Redshift, Snowflake, Azure SQL, PostgreSQL, MongoDB, MySQL, PL-SQL

Data Engineering - AWS Glue, Azure Data Factory, DBT, Apache Kafka, Spark, Hive, GCP Dataflow, ETL tools, ETL automation

Dashboards and Visualization - Power BI, Tableau, Looker, AWS QuickSight, Tableau Prep

ML and Data Science - Alteryx, RapidMiner

System Administration and Infrastructure - containers, containerized deployments, OpenShift PROFESSIONAL EXPERIENCE

Wells Fargo May 2025 – Present

Azure Data Engineer

Designed Azure Data Factory and Azure Databricks pipelines to ingest banking data, improving batch reliability, standardizing transformations, and accelerating governed delivery to business analysts.

Engineered Azure Synapse and ADLS integrations with Python and SQL, enabling scalable lakehouse processing, reusable data models, and dependable reporting across core finance domains.

Optimized Spark and PySpark workloads on Azure, reducing pipeline bottlenecks, strengthening data quality checks, and improving downstream consumption for operational reporting teams enterprisewide efficiently.

Standardized metadata, lineage, and access controls across Azure environments, aligning data governance requirements with secure ingestion patterns and trusted enterprise warehouse datasets consistently.

Automated CI/CD deployments through Azure DevOps, accelerating release cycles, minimizing manual errors, and improving observability for ETL workflows supporting critical regulatory reporting operations enterprisewide.

Engineered data processing automation and workflow automation by leveraging ETL tools, resulting in a 40% reduction in processing time and enhanced data-driven solutions across enterprise-level governance.

Orchestrated large-scale architecture initiatives and enterprise rollouts using containers and containerized deployments, achieving 99.9% uptime and ensuring scalability reliability in a shared services environment. Allied world Assurance Company July 2024 – April 2025 AWS Data Engineer

Integrated AWS Glue, S3, and Redshift pipelines to consolidate insurance data, improving ingestion resilience, curated warehouse availability, and downstream reporting accuracy enterprisewide consistently daily.

Configured EMR and Spark processing frameworks with Python and SQL, enabling scalable transformations, efficient batch execution, and reliable delivery of policy datasets across domains.

Validated data quality, lineage, and metadata controls across AWS environments, supporting governed analytics, auditable workflows, and trusted datasets for underwriting stakeholders consistently organizationwide daily.

Streamlined Airflow orchestration with Lambda, Athena, and Terraform, reducing operational overhead, improving job monitoring, and strengthening deployment consistency across cloud workloads consistently.

Analyzed Snowflake and Kafka integrations on AWS, resolving pipeline issues, optimizing throughput, and supporting timely access to business-critical insurance reporting data for stakeholders daily.

Architected CI/CD automation pipeline management and ETL automation, optimizing task dependency tuning scheduling scalability, saving 100+ engineering hours monthly and boosting operational insights.

Pioneered architecture design and cross-functional initiatives, utilizing PL-SQL and Alteryx, resulting in improved code quality and performance optimization across scrum teams. CGI January 2022 – July 2023

GCP Data Engineer

Orchestrated BigQuery, Dataflow, and Pub/Sub pipelines to process enterprise data, improving scalable analytics delivery, curated datasets, and reporting readiness for stakeholders consistently organizationwide daily.

Modernized Cloud Composer and dbt workflows with SQL and Python, enabling dependable transformations, reusable models, and faster access to governed analytical data across teams.

Established GCP IAM, metadata, and lineage controls across analytics platforms, strengthening secure access, data governance, and confidence in shared reporting assets enterprisewide consistently daily.

Delivered Looker and Tableau-ready datasets from BigQuery and Spark pipelines, improving dashboard performance, self-service analytics adoption, and business decision support across business functions organizationwide.

Refined data quality monitoring and observability across GCP integrations, resolving anomalies quickly, reducing rework, and supporting reliable analytics across cross-functional teams consistently.

Modernized mentor development teams and mentor guide teams by implementing batch processing tools and performance optimization strategies, enhancing leadership skills and reducing defect rates by 30%. Bupa July 2019 – December 2021

Data Engineer

Designed Azure Data Factory and Azure Databricks pipelines to ingest enterprise data, improving transformation consistency, batch reliability, and governed delivery for downstream analytics teams.

Engineered Azure Synapse, ADLS, Python, and SQL workflows to curate scalable datasets, enabling reusable models, trusted reporting, and efficient cross-functional data consumption across teams.

Optimized PySpark and Spark jobs on Azure Databricks, reducing processing bottlenecks, strengthening data quality validation, and accelerating availability of analytics-ready datasets for business users.

Standardized metadata, lineage, and access controls across Azure platforms, aligning governance requirements with secure ingestion patterns and dependable warehouse assets for reporting teams.

Automated CI/CD deployments through Azure DevOps, streamlining release processes, minimizing manual failures, and improving observability for ETL workflows supporting enterprise reporting across business units.

Revolutionized troubleshoot resolve performance issues in containers by deploying OpenShift, improving system efficiency and reducing latency of 1M+ requests by 20%. EDUCATION

Master's in Information technology - Wilmington University

Bachelor's in Electronics and Communication Engineering - Anurag University

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