Khadarvalli Phatan

Lead Data Modeler with 15+ years of experience designing scalable, high-performance data ecosystems for Tier-1 banks and global insurers.

Extensive expertise in enterprise data modeling using Erwin and FSLDM frameworks , enabling robust, governed data architectures across both cloud and on-premise environments.

Skilled in solving complex data integration, performance, and governance challenges leveraging Teradata, Snowflake, Azure, and Databricks .

Proven ability to identify inefficiencies, optimize data pipelines, and implement metadata-driven automation that enhances reporting accuracy and accelerates decision-making.

Strong problem-solver with a track record of transforming complex data challenges into scalable, performance-optimized, and business-aligned solutions .

• Data Warehousing

• Data Modelling

• Data Profiling

• Data Migration

• Performance Tuning

• Data Governance

• Workflow Automation

• Data Security

• Data Pipelines

• Predictive Analysis

• Data Mining

• Data Lakes

• Databricks Certified Data Engineer Professional 2025
• Snowflake Certified Data Engineer Associate 2025
• Teradata V2R5 Certified Professional 2012

Client : Chubb Corporation, USA

Project : Implementation of Personal Risk Services Data Models

Duration : Jan 2024 – May 2025

Role : Lead Data Modeller

Focus Area: Design and enhance data models to support a range of personal risk insurance products.

Technology: Erwin Data Modeler, Teradata 16, SQL Server, Azure Cloud Infrastructure

Responsibilities:

• Led Erwin-based data modelling sessions to create detailed documentation and lineage diagrams that improved governance and onboarding.
• Designed and documented enterprise data models aligned with FSLDM and regulatory requirements using Erwin.
• Developed conceptual, logical, and physical models for personal risk and claims data.
• Built automated data dictionaries and taxonomy integration pipelines on Azure Synapse, improving onboarding.
• Led a modelling team of 5; implemented model review processes to reduce rework by 20% and improve delivery consistency.
• Spearheaded Databricks pilot for behavioural segmentation; integrated scoring into analytics pipelines.

Client : ANZ Bank, Australia

Project : Implementation of Enterprise Profitability Solution

Duration : Mar 2019 – Dec 2023

Role: Senior Data Engineer

Focus Area: Designing and developing the Data Model framework to evaluate customer-level profitability across critical business segments.

Technology: Erwin Data Modeler, Teradata Vantage, Data Stage, Data Bricks, Snowflake, Oracle, Tableau

Responsibilities :

• Designed and implemented a customer-level profitability data model to support analytical and strategic initiatives across key business segments.
• Built scalable and reusable data models using Erwin Data Modeler, aligning with enterprise architecture and reporting needs.
• Leveraged Teradata Vantage to perform high-volume data processing and financial analysis, ensuring accurate profitability calculations.
• Developed ETL workflows in Databricks to integrate and transform complex transactional data into analytical datasets.
• Utilized Snowflake for efficient cloud-based storage and delivery of profitability insights across business units.
• Aligned technical models with business KPIs to track profitability trends at customer, product, and segment levels.
• Enabled data-driven decision-making by providing timely, trusted, and granular profitability insights to finance and strategy teams.
• Resulted in improved customer segmentation, targeted product offerings, and better capital allocation, enhancing overall profitability and business performance

Client : Mass Mutual Insurance Info delivery, USA

Project : Implementation of Teradata best practices across development and administrative environments of Insurance applications.

Duration : Feb 2012 – Jan 2014 | Apr 2017 – Mar 2019

Role: Data Engineer

Focus Area: Leading the design and implementation of advanced Teradata best practices to optimise data architecture, enhance system performance, and ensure scalable, maintainable solutions aligned with enterprise standards.

Technology: Teradata, Informatica Power Centre, SQL Server

Responsibilities :

• Standardized naming conventions, indexing strategies, and partitioning for Teradata environments.
• Collaborated with DBA team to optimize workload management (TASM), reducing system resource conflicts.
• Enhanced metadata capture processes, improving audit traceability for compliance.

Client : AIA, Thailand

Project : Implementation of Anti Money Laundering

Duration : Feb 2014 – Mar 2017

Role: Data Engineer

Focus Area: Designed and developed the ETL framework to provision essential business data for the broad integration of the Anti-Money Laundering (AML) solution.

Technology: Teradata, Informatica Power Centre, SQL Server, Oracle, DB2, Sybase

Responsibilities :

• Led the design of AML data feeds to meet regulatory monitoring thresholds.
• Coordinated with fraud analytics teams to ensure real-time detection rules had consistent and reliable data.
• Built data lineage documentation that reduced onboarding time for new team members by 25%.

Client : Lloyds Bank, UK

Project : EDW Application Development

Duration : Nov 2009 – Feb 2012

Role: Data Engineer

Focus Area: Developed application code to support the integration of Bank of Scotland and Halifax Bank into Lloyds Banking Group, leveraging Teradata BTEQ and Teradata SQL for seamless data consolidation.

Technology: Teradata, Informatica Power Centre, SQL Server, Oracle, DB2, Sybase

Responsibilities :

• Worked on merging 50+ legacy data feeds into Lloyds EDW with minimal disruption to BAU reporting.
• Supported parallel run validation during data migration, ensuring
• Collaborated with cross-functional teams (BI, Risk, Ops) to deliver enterprise single customer view (SCV).

• Enterprise Data Modeling: Delivered FSLDM-based enterprise models that reduced redundancy and improved ETL efficiency across multiple clients.
• Performance Tuning: Optimized Teradata workloads, improving system efficiency and reducing operational costs by up to 40%.
• Data Governance: Defined and enforced standards improving data quality & compliance for banking/insurance clients.
• Automation & CI/CD: Implemented GitHub + Bamboo workflows reducing deployment errors by >50%.
• Cloud Migration Success: Designed migration roadmaps from on-prem Teradata to Snowflake & Azure, cutting infrastructure costs while improving scalability.