Praveen Kumar Katragunta
PRAVEEN KATRAGUNTASR. DATA ENGINEER // RABOBANK
// CLOUD DATA PLATFORM 01
🟢 1TB+ DAILY DATA // 99.9% RELIABILITY
AZURE DATABRICKS & PYSPARK LAKEHOUSE ARCHITECTURE

SENIOR DATA ENGINEER

5+ years delivering cloud-scale enterprise data platforms. Currently driving data platform transformation for Rabobank Netherlands, designing pipelines processing 1TB+ daily data with 99.9% reliability, achieving 40% Spark performance gains and 25% cost reduction.

TECH: AZURE DATABRICKS / PYSPARK / SPARK SQL / DELTA LAKEVIEW EXPERIENCE
Praveen Kumar Katragunta
STATUS: 5+ YRS EXPBENGALURU, INDIA
SENIOR DATA ARCHITECT
PRAVEEN KUMAR KATRAGUNTA
SCROLL OR SCRUB TIMELINE
// ROOT 02 — ARCHITECT PROFILE
SEEKING SENIOR DATA ENGINEER / DATABRICKS ROLES

Senior Data Engineer specializing in Azure Databricks, PySpark, and enterprise Lakehouses.

Senior Data Engineer with 5+ years of experience delivering cloud-scale data platforms on Microsoft Azure, specializing in Databricks, PySpark, and Lakehouse architectures. Currently working with Rabobank Netherlands, designing and optimizing data pipelines processing 1TB+ daily data with 99.9% reliability, achieving 40% performance improvements and 25% cost reduction.

Bengaluru, India (Open to Global / Remote)B.Tech in Computer Science (JNTUA)
EXPERIENCE5+ YEARS
SPARK PERFORMANCE GAINS+40%
CLOUD COST REDUCTION-25%
DATA PIPELINE UPTIME99.9%
PRIMARY DOMAIN
Azure Databricks & Lakehouse
PySpark / Medallion Architecture
SCALE & RELIABILITY
1TB+ Daily Data Processing
99.9% Pipeline Reliability
DATA GOVERNANCE
Unity Catalog & GDPR
100% Financial Compliance
GLOBAL CONSULTING
Netherlands Onsite Experience
Rabobank (Utrecht) & Microsoft
// TECH STACK 03 — TOOLCHAIN & ARCHITECTURE

Data Engineering & Cloud Ecosystem

Proven end-to-end tooling across Big Data pipelines, Medallion Lakehouses, infrastructure automation, and data governance.

🧱Azure DatabricksBig Data
⚡PySparkProcessing
🔍Spark SQLQuerying
🏅Delta Lake & MedallionArchitecture
🏭Azure Data Factory (ADF)ETL / ELT
📊Azure Synapse AnalyticsData Platform
💾Azure Data Lake (ADLS Gen2)Storage
🐍PythonLanguage
🗄️SQLDatabase
💻C#Language
🧱Azure DatabricksBig Data
⚡PySparkProcessing
🔍Spark SQLQuerying
🏅Delta Lake & MedallionArchitecture
🏭Azure Data Factory (ADF)ETL / ELT
📊Azure Synapse AnalyticsData Platform
💾Azure Data Lake (ADLS Gen2)Storage
🐍PythonLanguage
🗄️SQLDatabase
💻C#Language
🧱Azure DatabricksBig Data
⚡PySparkProcessing
🔍Spark SQLQuerying
🏅Delta Lake & MedallionArchitecture
🏭Azure Data Factory (ADF)ETL / ELT
📊Azure Synapse AnalyticsData Platform
💾Azure Data Lake (ADLS Gen2)Storage
🐍PythonLanguage
🗄️SQLDatabase
💻C#Language
🛡️Unity CatalogGovernance
⚙️Azure DevOps (YAML)CI/CD
🌍TerraformIaC
🐙GitVersion Control
🌪️Apache AirflowOrchestration
⚡Power AutomateAutomation
📜GDPR ComplianceStandards
🏷️Collibra & KenshoData Catalog
✅Great ExpectationsData Quality
📈Power BIVisualization
🛡️Unity CatalogGovernance
⚙️Azure DevOps (YAML)CI/CD
🌍TerraformIaC
🐙GitVersion Control
🌪️Apache AirflowOrchestration
⚡Power AutomateAutomation
📜GDPR ComplianceStandards
🏷️Collibra & KenshoData Catalog
✅Great ExpectationsData Quality
📈Power BIVisualization
🛡️Unity CatalogGovernance
⚙️Azure DevOps (YAML)CI/CD
🌍TerraformIaC
🐙GitVersion Control
🌪️Apache AirflowOrchestration
⚡Power AutomateAutomation
📜GDPR ComplianceStandards
🏷️Collibra & KenshoData Catalog
✅Great ExpectationsData Quality
📈Power BIVisualization
// LIVE ARCHITECTURE // MEDALLION BLUEPRINT

Interactive Medallion Lakehouse Architecture

Click through each pipeline tier to inspect how 1TB+ daily financial data transitions from raw ingestion to enterprise reporting layers.

INSPECTING: SILVER LAYER (CLEANSED)

PySpark Deduplication & Validation

Cleansed, normalized, and schema-enforced Delta Lake tables. Complex join logic tuned using broadcast hashes and Z-ordering to strip duplicates and enforce banking GDPR rules.

Broadcast joins and intelligent cluster caching
Dynamic data quality verification via Great Expectations
Row and column-level masking with Unity Catalog
TECH STACK:Azure Databricks / PySpark / Great Expectations
PERFORMANCE SLA40% Optimized Runtime
DATA GOVERNANCEUnity Catalog Active
DEPLOYMENT STATUSProduction Monitored
CLIENT VERIFIED: RABOBANK NETHERLANDS● 99.9% UPTIME
// TRACK RECORD 05 — ENTERPRISE EXPERIENCE

Work Experience & Impact

5+ YEARS DELIVERING PRODUCTION CLOUD PLATFORMS

Senior Data Engineer

AccentureClient: Rabobank, Netherlands
15/01/2024 – PresentBengaluru, India (1-Month Onsite in Utrecht, Netherlands)
IMPACT METRICS
+40% Perf / -25% Cloud Cost

Designed and optimized end-to-end data pipelines for Rabobank on Azure Databricks using PySpark and SQL, processing over 1TB of daily transactional data while maintaining 99.9% pipeline reliability within a Medallion Architecture.

Developed, scheduled, and monitored Databricks notebooks, jobs, and workflows for batch and incremental data processing.

Designed Lakehouse architectures and data models to support analytics, reporting, and downstream data consumption.

Improved data processing performance by 40% and reduced cloud infrastructure costs by 25% through advanced Spark tuning (broadcast joins, caching, partitioning) and query optimization.

Implemented enterprise-grade data governance for sensitive financial datasets using Unity Catalog, ensuring 100% compliance with GDPR and banking security standards across multiple production environments.

Supported Rabobank stakeholders during a 1-month onsite assignment in Utrecht, Netherlands, collaborating with local Dutch engineering teams to deliver data products 15% faster while maintaining 98% data accuracy.

Automated data platform deployments using Azure DevOps CI/CD (YAML pipelines), enabling version-controlled and repeatable releases across environments.

Azure DatabricksPySparkSpark SQLMedallion ArchitectureUnity CatalogGDPRAzure DevOpsYAML CI/CDDelta Lake

Data Engineer

LTI MindtreeClient: Microsoft
28/12/2020 – 14/01/2024Bengaluru, India
SCOPE OF WORK
Enterprise Azure Platform

Built scalable end-to-end data pipelines using Azure Data Factory (ADF) and Azure Synapse Analytics to process large-scale datasets with high reliability.

Implemented cloud infrastructure automation and CI/CD using Terraform and Azure DevOps, ensuring consistent deployments across environments.

Worked directly with Microsoft internal teams as a client-facing Data Engineer, contributing to Azure-based data platforms and aligning solutions with Microsoft engineering standards and best practices.

Supported Azure data platform initiatives for a Microsoft enterprise client, following Microsoft-recommended architecture patterns, security standards, and performance guidelines.

Optimized SQL queries to improve performance and reduce system load, while providing technical guidance and mentorship to support team knowledge sharing.

Azure Data FactoryAzure Synapse AnalyticsAzure Data LakeTerraformAzure DevOpsSQL OptimizationCI/CDKey Vault
// CREDENTIALS 04 — INDUSTRY CERTIFICATIONS

Verified Professional Certifications

Certified technical authority across Databricks Big Data engineering and Microsoft Azure cloud infrastructure.

Databricks
PROFESSIONAL CREDENTIAL

Databricks Certified Data Engineer Professional

Microsoft
ASSOCIATE CERTIFIED

Microsoft Certified: Azure Data Engineer Associate

EXAM CODEDP-203
Databricks
ASSOCIATE CREDENTIAL

Databricks Certified Data Engineer Associate

Microsoft
CLOUD AI CREDENTIAL

Microsoft Certified: Azure AI Fundamentals

EXAM CODEAI-900
// ARCHITECTURES 04 — SELECTED ENTERPRISE PLATFORMS

Featured Data Engineering Systems

PRODUCTION VERIFIED ARCHITECTURES
Enterprise Multi-Hop Lakehouse & Spark Optimizer
// INITIATIVE 011TB+/day • 99.9% SLA
40% Spark Optimization
// SYSTEM: RABOBANK-MEDALLION-LAKEHOUSE

Enterprise Multi-Hop Lakehouse & Spark Optimizer

Designed and deployed end-to-end multi-hop Medallion data pipelines on Azure Databricks with PySpark and Delta Lake. Implemented broadcast joins, Z-ordering, query optimization, and caching, generating a 40% performance gain and 25% cloud infrastructure cost reduction.

Azure DatabricksPySparkDelta LakeSpark SQLAzure Data Lake Gen2
THROUGHPUT & UPTIME
VIEW SPECS
Unity Catalog & Banking Security Compliance Engine
// INITIATIVE 02100% GDPR Compliant
Enterprise Unity Catalog
// PLATFORM: FINANCIAL-DATA-GOVERNANCE

Unity Catalog & Banking Security Compliance Engine

Engineered centralized access controls, fine-grained row/column-level data masking, and automated lineage tracking across multi-tenant financial environments at Rabobank. Collaborated on-site in Utrecht, Netherlands with local teams.

Unity CatalogAzure Key VaultCollibraKenshoGreat Expectations
AUDIT ACCURACY
VIEW SPECS
Scalable ETL/ELT Platform for Microsoft Ecosystem
// INITIATIVE 03100% Automated CI/CD
Terraform + Azure DevOps
// PIPELINES: AZURE-ENTERPRISE-SYNAPSE

Scalable ETL/ELT Platform for Microsoft Ecosystem

Constructed resilient cloud data pipelines using Azure Data Factory and Synapse Analytics. Automated multi-environment infrastructure provisioning with Terraform and streamlined release pipelines with Azure DevOps YAML.

Azure Data FactoryAzure SynapseTerraformAzure DevOpsSQL Server
DEPLOYMENT SPEED
VIEW SPECS
Automated Data Quality & Batch/Stream Orchestration
// INITIATIVE 0498% Target Accuracy
Airflow + Databricks Jobs
// AUTOMATION: WORKFLOW-ORCHESTRATOR

Automated Data Quality & Batch/Stream Orchestration

Configured Databricks Workflows, scheduled jobs, and Airflow DAGs for reliable batch ingestion and near-real-time streaming. Automated alerting, validation rules, and self-healing pipeline fallbacks.

Databricks WorkflowsApache AirflowPythonPower BIPower Automate
DATA ACCURACY
VIEW SPECS
// DISPATCH 06 — CONNECT & ENGAGE

Get In Touch with Praveen

Currently open to Senior Data Engineer and Databricks Lakehouse roles in product-based or global data-driven organizations.

candidate-dispatch-profile.json
// TELEMETRY LIVE STREAM // ENCRYPTED DISPATCH PACKET
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  "recipient": "Praveen Kumar Katragunta",
  "credentials": "Databricks Certified Professional / Azure DP-203",
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    "website": "https://praveenkatragunta.com"
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    "timestamp": "2026-09-21T00:00:00.000Z",
    "target_availability": "Actively interviewing for Senior Data / Lakehouse roles"
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STATUS: READY_FOR_DISPATCH
PORT: 443 / SSL