Principal Data Architect

UST; Thiruvananthapuram; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

UST in India is seeking a seasoned Principal Data Architect to lead design, governance, and modernization of enterprise data platforms. You will drive the transformation of fragmented sources into a unified data model and establish a single source of truth to enable analytics and operations.

You will define data standards, metadata frameworks, and migration strategies, while guiding analytics teams, solution architects, and engineers toward scalable cloud-based architectures such as Snowflake,

Qualifications

• 12+ years of experience in data architecture, modeling, governance, and migration.
• Proven ability to lead complex data modernization in regulated environments.

Responsibilities

• Lead the design, governance, and modernization of enterprise data platforms.
• Define Golden Record, source-to-target mapping, and metadata management strategies.
• Architect relational, dimensional, and vault-based data models and cloud data platforms.
• Provide technical guidance across analytics, engineering, and business teams.

Skills

Data Architecture

Data Modeling

Data Governance

Data Migration

SQL

Python

Pandas

OpenPyXL

Regex

Data Quality

Data Lineage

Cloud Data Platforms

Tools

Snowflake

Databricks

Data Lakes

Lakehouse

Job description

Role Description

Principal Data Architect (Data Modeling & Migration)

Role Overview

We are seeking a highly experienced Principal Data Architect to lead the design, governance, and modernization of enterprise data platforms. This role will act as the primary authority for data architecture, driving the transformation of fragmented legacy data sources, including Excel files, Word documents, and siloed applications, into a scalable and governed Unified Data Model. The successful candidate will define the organization's Single Source of Truth, establish data standards and governance frameworks, and create the foundational architecture that supports operational workflows, system integrations, and advanced analytics initiatives.

Key Responsibilities

Data Discovery & Strategy

• Analyze and assess legacy data sources, including spreadsheets, documents, and disconnected systems, to uncover business rules, data relationships, and process dependencies.
• Conduct data profiling and quality assessments to identify inconsistencies, duplication, and structural issues before migration.
• Define Golden Record and master data management strategies to ensure consistency across multiple systems.
• Develop Source-to-Target Mapping (STTM) documents and transformation specifications for integration and orchestration teams.
• Establish metadata management, governance, and version control frameworks to support long‑term data integrity.

Enterprise Data Modeling

• Design and maintain robust relational data models (3NF) to support transactional and operational business processes.
• Architect modern Data Warehouse, Lakehouse, Star Schema, Snowflake Schema, or Data Vault solutions to enable enterprise reporting and analytics.
• Define scalable and extensible data structures that support future system integrations and evolving business requirements.
• Implement data lineage, auditing, and traceability frameworks to ensure complete visibility from source to consumption.

Data Migration & Modernization

• Lead the architecture and migration strategy for historical and active data from legacy systems into modern cloud‑based platforms.
• Design data transformation rules, migration approaches, and validation mechanisms to ensure data accuracy and consistency.
• Collaborate with Solution Architects, Business Analysts, and Engineering teams to align data architecture with broader technology objectives.
• Provide technical guidance and business‑rule definitions to integration and orchestration teams.

Technical Leadership

• Serve as the organization's subject matter expert and decision‑maker for data architecture, modeling, governance, and migration initiatives.
• Anticipate and mitigate data quality, consistency, and schema‑evolution challenges across complex environments.
• Promote best practices in enterprise data management, cloud architecture, and data governance.
• Translate business challenges into scalable technical solutions and implementation roadmaps.

Experience

Required Skills & Experience

• 12+ years of experience in Data Architecture, Data Modeling, Data Governance, and Data Migration.
• Proven success working within complex, highly regulated, and data‑intensive environments.

Data Modeling Expertise

• Expert knowledge of OLTP and OLAP data modeling techniques.
• Strong experience with:
  • Normalized relational models (3NF)
  • Dimensional modeling
  • Star Schema
  • Snowflake Schema
  • Data Vault methodologies
  • Lakehouse architecture patterns

Data Analysis & Profiling

• Advanced proficiency in SQL and Python for data discovery, profiling, and analysis.
• Hands‑on expertise with:
  • Pandas
  • OpenPyXL
  • Regex
  • Data quality assessment and remediation

Cloud Data Platforms

• Extensive experience designing modern cloud‑based data ecosystems using:
  • Snowflake
  • Databricks
  • Data Lakes and Lakehouses
  • Medallion Architecture

Integration & Data Engineering

• Strong understanding of:
  • Metadata‑driven ETL/ELT frameworks
  • API integrations
  • JSON/XML processing and transformation
  • Data lineage and traceability frameworks
  • Data migration and modernization strategies

Preferred Qualifications

• Experience establishing enterprise‑wide data governance and master data management frameworks.
• Strong stakeholder management and communication skills.
• Ability to bridge business requirements and technical architecture decisions.
• Experience mentoring architects, engineers, and data teams.
• Familiarity with clinical, healthcare, life sciences, financial, or other regulated industries is highly desirable.

Skills

Data Architect, Data Modeling, OLTP, Python, ETL, Data Lakes, Master Data Management, Pandas, Snowflake, Data Governance, Data Vault, Data Validation