Senior Cloud Data Engineer with Cloud-Native Expertise

Sai Divya Kamepalli

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

Mobile: 424-***-****

LinkedIn: www.linkedin.com/in/divyakamepalli

Senior Data Engineer

PROFESSIONAL SUMMARY

Architected robust cloud data solutions across Azure, AWS and GCP over five years, delivering reliable pipelines, warehouses and analytics products for enterprise stakeholders.

Engineered batch and streaming data pipelines with Python, SQL, Spark and Airflow, improving data quality, observability and consumption for reporting and data science.

Designed scalable lakehouse architectures on Snowflake, Databricks and BigQuery, integrating diverse enterprise sources to support self-service analytics, business dashboards and regulatory reporting needs.

Optimized ELT frameworks, data models and governance practices, collaborating with teams to standardize definitions, reduce duplication and accelerate delivery of trusted analytical datasets.

Mentored and guided teams to achieve project goals, resulting in a 20% increase in productivity.

Facilitated collaboration among departments, enhancing communication and reducing project completion time by 15%.

Leveraged leadership skills to inspire and motivate team members, improving overall team performance and morale.

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), OpenShift

Infrastructure As Code - Terraform, Ansible, ARM Templates, Bicep, CloudFormation, Jenkins, Azure DevOps

Monitoring And Incident Response - New Relic, AWS CloudWatch, Azure Monitor, ServiceNow, RCA, SLA Management, troubleshoot, resolve performance issues

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

Ci/Cd And Devops - Jenkins, GitHub Actions, Git, GitLab, CodePipeline, CI/CD Pipelines, Shell Scripting Programming & Scripting - Python, SQL, Bash, PowerShell, automation pipeline management

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

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

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

Programming Languages - .py (Python)

Tools And Platforms - Alteryx, RapidMiner

Software Architecture - large-scale architecture initiatives, enterprise rollouts

System Administration And Infrastructure - containers, containerized deployments PROFESSIONAL EXPERIENCE

AbbottInc January 2024 – Present

Senior Data Engineer

Built Azure Data Factory pipelines feeding ADLS and Azure Synapse, establishing automated ingestion from banking systems and improving data freshness for Trust reporting.

Implemented data models in Azure Synapse and Azure SQL, aligning schemas with business stakeholders and reducing reconciliation issues across regulatory and reporting domains.

Developed Azure Databricks notebooks with Python and Spark, transforming datasets into curated marts that accelerated analytics turnaround time for risk and treasury teams.

Streamlined batch schedules and monitoring on Azure Databricks and Azure Data Factory, tightening SLAs, reducing pipeline failures and stabilizing dashboards consumed by leadership.

Automated Power BI refreshes on Azure Synapse views, improving transparency of critical liquidity metrics and enabling timely compliance evidence required by external auditors.

Developed and optimized data preparation and orchestration processes, enhancing data integration speed by 40% and improving overall workflow automation efficiency.

Led architecture design and data processing automation projects, resulting in a 50% reduction in manual processing time and improved system performance optimization.

Implemented code quality and operational insights strategies, enhancing enterprise-level governance and ensuring high standards across development teams.

Demonstrated leadership skills by mentoring and guiding teams, fostering collaboration and achieving a 25% increase in project delivery speed.

Northern Trust January 2023 – December 2023

Data Engineer

Orchestrated AWS Glue and Apache Airflow workflows ingesting data from S3 and relational sources into AWS Redshift, strengthening analytics foundations for AbbottInc operations.

Integrated streaming data from Kinesis with batch datasets on AWS EMR and Spark, delivering features powering AbbottInc forecasting, pricing and commercial analytics initiatives.

Configured Redshift schemas, sort keys and distribution strategies, tuning SQL workloads and accelerating AbbottInc reporting performance on financial, supply chain and manufacturing dashboards.

Modernized ETL jobs into ELT pipelines on AWS using Glue, Lambda and Step Functions, reducing failures and simplifying change management across AbbottInc deployments.

Consolidated disparate AbbottInc data marts into Snowflake on AWS, enforcing data governance, improving metric consistency and enabling trusted self-service insights for business stakeholders.

Utilized .py (Python) and PL-SQL to develop and maintain data integration pipelines, improving data accuracy by 30% and streamlining ETL processes.

Leveraged Alteryx and RapidMiner for advanced data analytics, enabling actionable insights and reducing analysis time by 35%.

Utilized Tableau Prep and OpenShift to facilitate containerized deployments and troubleshoot data visualization issues, enhancing reporting efficiency by 20%.

Designed and managed automation pipeline management and large-scale architecture initiatives, leading to successful enterprise rollouts and improved scalability. Accenture June 2020 – July 2022

Data Engineer

Enhanced GCP ingestion frameworks by building Dataflow pipelines landing curated datasets in Google BigQuery, supporting Accenture reporting, experimentation and advanced data analytics scenarios.

Standardized BigQuery dimensional models and semantic layers powering Looker and Tableau dashboards, ensuring consistent KPIs and accelerating generation for marketing and operations leadership.

Coordinated cross-region BigQuery workloads, optimizing partitioning, clustering and materialized views to control costs while preserving interactive performance for high-volume analytical queries, improving latency.

Analyzed sales and operational datasets with SQL and Python in BigQuery, crafting reusable metrics layers and improving accuracy of forecasting and segmentation initiatives.

Validated data quality through automated BigQuery checks and reconciliation views, increasing trust in analytics and enabling adoption of AI solutions across Accenture engagements.

Implemented containers and containerized deployments to enhance system scalability, reducing deployment time by 40% and improving resource utilization.

Collaborated with scrum teams to troubleshoot and resolve performance issues, optimizing task dependency tuning and scheduling for improved project timelines.

Enhanced shared services environment through cross-functional initiatives, fostering a collaborative culture and achieving a 30% increase in team productivity.

EDUCATION

Master's in Computer Science - University of Wisconsin at Milwaukee

Bachelor's in Information Technology – Siddhartha Institution

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