Senior Data Engineer - Cloud, Data Pipelines, CI/CD Expert

Hyndhavi Sibbala

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

Mobile: 682-***-****

LinkedIn: https://www.linkedin.com/in/hyndhavis

Senior Data Engineer

PROFESSIONAL SUMMARY

Architected secure multi-cloud data engineering solutions over four years, building robust pipelines across Azure, AWS, and GCP with Python, SQL, Spark, and Databricks.

Engineered batch and streaming workflows using Airflow, Kafka, Azure Data Factory, AWS Glue, and BigQuery, significantly improving data reliability, observability, and platform performance.

Developed dimensional data models on Snowflake, Redshift, and Synapse, enabling scalable analytics and self- service reporting through Power BI, Tableau, and business intelligence tools.

Strengthened data quality, governance, and automation by applying CICD, Git-based workflows, and rigorous validation, supporting compliant, well-documented data platforms for advanced analytics initiatives.

Mentored and guided teams to enhance productivity and fostered a culture of continuous improvement.

Collaborated with cross-functional teams to streamline processes and improve project delivery timelines.

Exercised leadership skills to resolve team conflicts, boosting morale and enhancing collaboration. 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), Microsoft Fabric, 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

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

Data Analytics And Tools - Alteryx, RapidMiner

Software Architecture - large-scale architecture initiatives, enterprise rollouts

System Administration And Infrastructure - containers, containerized deployments

Technical Support And Troubleshooting - resolve performance issues PROFESSIONAL EXPERIENCE

Northern Trust March 2025 – Present

Senior Data Engineer

Designed Azure Data Factory pipelines integrating Azure Data Lake Storage and Databricks, delivering reliable financial datasets powering downstream reporting and regulatory analytics workflows.

Built parameterized PySpark jobs on Azure Databricks to transform transactional feeds into curated Delta Lake tables supporting performance dashboards and intraday risk monitoring.

Implemented Azure Synapse data models combining SQL pools and serverless views to unify operational, reference, and market data for analytical consumption at scale.

Optimized Azure Blob Storage layouts, partitioning, and compression strategies, reducing data processing runtimes while lowering cloud storage expenses across critical enterprise reporting workloads.

Automated end-to-end Azure data quality checks with Python, SQL, and metadata-driven rules, improving timeliness, accuracy, and auditability for finance and risk reporting processes.

Led data preparation and orchestration efforts, enhancing data accuracy and reducing processing time by 25% through streamlined workflows.

Designed and implemented integration and workflow automation solutions, improving data consistency and reducing manual intervention by 40%.

Architected scalable architecture design and data processing automation, supporting a 50% increase in data throughput and improving system reliability.

Executed performance optimization and code quality initiatives, resulting in a 30% reduction in system latency and improved maintainability.

Improved system scalability and provided operational insights, enabling a 20% increase in resource efficiency and informed decision-making.

Zoom January 2024 – February 2025

Data Engineer

Streamlined ingestion of Zoom telemetry by orchestrating AWS Glue jobs and Lambda functions, loading S3 landing data into curated Redshift schemas for analytics.

Integrated AWS Kinesis streams with EMR Spark applications to process near real-time collaboration events, improving monitoring, alerting, and troubleshooting for customer experience teams.

Configured Athena query workflows and reusable SQL templates over partitioned S3 data lakes, enabling product managers to explore adoption trends and usage patterns.

Validated ETL pipelines with Python and SQL unit tests on AWS, detecting schema drift and safeguarding reporting for billing, compliance, and executive dashboards.

Analyzed platform usage datasets combining Redshift, Athena, and external CRM exports, uncovering insights that informed roadmap decisions and targeted customer engagement initiatives globally.

Exhibited leadership skills to mentor and guide teams, fostering a collaborative environment that increased project delivery speed by 15%.

Collaborated with teams using PL-SQL and Alteryx to streamline data workflows, enhancing data processing efficiency by 35%.

Utilized RapidMiner and Tableau Prep to create data integration pipelines, reducing data preparation time by 40%.

Deployed applications on OpenShift and managed ETL tools, ensuring seamless containerized deployments and enhancing system uptime by 20%.

Managed automation pipeline management and large-scale architecture initiatives, supporting enterprise rollouts and increasing deployment frequency by 30%.

Accenture September 2021 – July 2023

Data Engineer

Orchestrated GCP streaming data pipelines leveraging Dataflow and BigQuery to ingest global customer interaction data, supporting scalable analytics for marketing and operations teams.

Standardized data models in BigQuery using dbt and dimensional design, enabling consistent KPIs across enterprise analytics programs and accelerating dashboard development for stakeholders.

Enhanced analytical datasets by blending BigQuery warehouse tables with APIs and flat files, enriching accurate revenue forecasting, churn analysis, and client profitability reporting.

Consolidated reporting into unified Looker and Power BI dashboards connected to GCP, giving leadership visibility into delivery performance, utilization, and strategic initiative progress.

Modernized SQL-based reports by rebuilding GCP-native analytics solutions with scheduled queries, data quality checks, and views tailored for self-service exploration by business analysts.

Implemented containers and containerized deployments to resolve performance issues, achieving a 25% improvement in application response times.

Facilitated scrum teams in a shared services environment, enhancing cross-functional collaboration and reducing project timelines by 10%.

Developed enterprise-level governance frameworks, ensuring compliance and reducing risk exposure by 15%.

Optimized task dependency tuning and scheduling, improving workflow efficiency and reducing execution time by 20%.

EDUCATION

Masters in Mathematics and computer science - University of Texas, Arlington

Bachelors in computer science engineering - Lendi Institute of engineering technology

Contact this candidate