Pradeep

Microsoft Certified Azure Data Architect with 14+ years of IT experience, including 8+ years architecting enterprise-scale cloud data platforms on Microsoft Azure. Deep expertise in Azure Data &

• AI services – Analytics, Databases, AI/ML, and IoT (Subject Matter Expert in Databricks &

• Fabric). Expert in translating complex analytical requirements into end-to-end technical designs, having architected and delivered 20+ production data platforms across Plan, Design, Build, and Deploy phases. Proven ability to design data models, ETL/ELT pipelines, dimensional data warehouses, and self-service analytics solutions on both relational (Azure SQL, Synapse) and non-relational (Cosmos DB) databases. Specialized in modern data architectures using medallion (Bronze/Silver/Gold) patterns, Azure Lakehouse (Fabric &

• Databricks), and enterprise data warehousing. Deep expertise in Delta Lake, Delta Live Tables (DLT), and scalable batch/real-time pipelines using Spark, Python, Kafka, and Event Hubs. Strong background in data governance, security, and compliance frameworks using Unity Catalog, Microsoft Purview, RBAC, row-level security, and masking. Established enterprise data governance standards covering data ownership, stewardship, quality, master data management, and fine-grained access control. Expert in CI/CD, Infrastructure-as-Code, and DevOps practices – Implemented GitHub, Azure DevOps CI/CD pipelines, static code analysis, test-driven development, and Infrastructure-as-Code (ARM Templates, Terraform, DABS) across multi-environment deployments (DEV/STG/PRD). Trusted technical leader and strategic advisor – Recommended forward-looking technology visions aligned with business transformation goals. Drove enterprise platform adoption through comprehensive change management—achieved 95% organizational buy-in from 50+ stakeholders. Recognized as a top Microsoft community contributor – 100K+ reputation in Azure Data &

• AI topics, Databricks Gold member, and Microsoft Global Hackathon winner.

Data & AI Engineering Architect - Phillips 66

(2024-12)

Led cross-functional teams of 15+ data engineers, 10+ data scientists, and 5+ analysts to deliver production-grade data and AI solutions aligned to business outcomes. Achieved 95% on-time delivery across 8 major initiatives and managed 50+ end-to-end production projects across multi-environment deployments. Architected and delivered secure, scalable, cloud-native data platforms on Microsoft Azure using Databricks, Fabric, Azure Data Lake Gen2, Azure SQL Database, and Azure Cosmos DB.

Achieved $150K+ annual cost savings through intelligent architecture design.

• Designed and implemented Delta Live Tables (DLT) for automated data quality validation and real-time monitoring. Optimized Spark performance across computing paradigms (in-memory, distributed, massively parallel processing).
• Established enterprise data governance and security frameworks including RBAC, row-level security, and masking. Deployed logging and monitoring across integration points.
• Drove adoption of Azure DevOps, CI/CD pipelines, and Infrastructure-as-Code practices using DABS (Databricks Automation Bundles).

Data & AI Engineering Architect - Microsoft

(2018-10 - 2024-12)

Successfully delivered 15+ large-scale data management initiatives. Architected platforms handling 2TB+ daily data ingestion serving 500+ enterprise users with 95%+ availability.

• Architected enterprise data platforms using Microsoft Fabric with medallion patterns. Led end-to-end Fabric setup, ELT ingestion, semantic model-driven BI with Direct Lake, governance frameworks, and on-premises to cloud migrations.
• Designed and implemented Delta Live Tables for automated data quality validation. Created real-time streaming pipelines with Event Hubs, Kafka, and Stream Analytics.
• Optimized Spark performance—reduced query latency from 45+ minutes to 8-10 minutes (82% improvement) across computing paradigms using intelligent partitioning, caching, and continuous monitoring.
• Configured Unity Catalog for centralized governance. Developed Purview-based compliance frameworks implementing lineage, automated classification, cataloging, and regulatory controls.
• Recommended forward-looking strategic technology visions and architecture roadmaps aligned with business transformation goals. Created and shared best practices documentation and reference architectures.

Azure Cloud Engineer - Microsoft

(2016-02 - 2018-09)

Supported enterprise customers deploying 20+ Azure data services. Provided technical architecture guidance on data platform modernization, helping 20+ organizations transition to cloud infrastructure. Built deep expertise in Azure architecture, data services, and cloud-native solution design; established best practices for scalability, security, and cost optimization.

Big Data Engineer - ISM University of Skills

(2014-02 - 2016-02)

Designed and maintained large-scale Hadoop ecosystems (HDFS, Hive, HBase, Spark, Sqoop). Developed ETL processes and data transformation pipelines supporting enterprise analytics and reporting.

Bachelor of Technology - B. Tech - JNTU Hyderabad (2013)