Job Description - Data Governance & Data Management Specialist

Experience

7-10 Years

Role Overview

We are looking for an experienced Data Governance & Data Management Specialist with strong hands-on expertise in data governance, data quality, metadata management, data lineage, MDM, and modern cloud data platforms.

The ideal candidate will combine data governance strategy with practical implementation skills, working closely with business, technology, data engineering, security, and compliance teams to establish governance standards and deliver high-quality, trusted, and compliant data assets.

The candidate should also have exposure to Agentic AI and understand how governance, metadata, data quality, and security can support enterprise AI initiatives.

Key Responsibilities

1. Data Governance & Management

Implement and operationalize enterprise Data Governance frameworks, policies, standards, and controls.
Establish data governance standards, principles, guardrails, processes, and operating models.
Define and maintain data ownership, stewardship, accountability, and governance roles.
Develop governance processes aligned with business, regulatory, privacy, and compliance requirements.
Work with business and technology stakeholders to identify critical data elements and establish governance controls.
Support implementation of Data Governance Operating Models across business domains.

2. Data Catalog, Metadata & Lineage

Hands-on experience with governance platforms such as Informatica, Collibra, or equivalent tools.
Build and maintain enterprise data catalogs, business glossaries, technical metadata, and data dictionaries.
Implement and manage end-to-end data lineage across source systems, data platforms, transformations, and consumption layers.
Define metadata management processes and standards.
Establish relationships between business terms, technical assets, data owners, policies, and data quality rules.
Support metadata-driven governance and data discovery initiatives.

3. Data Quality

Define and implement Data Quality (DQ) frameworks, rules, controls, and KPIs.
Establish DQ dimensions including accuracy, completeness, consistency, timeliness, uniqueness, and validity.
Develop and execute data quality rules using Informatica, Collibra, Snowflake, SQL, or equivalent technologies.
Analyze DQ issues, identify root causes, and coordinate remediation with data owners and engineering teams.
Develop DQ dashboards, scorecards, exception reports, and remediation processes.
Establish continuous data quality monitoring and improvement mechanisms.

4. Master Data Management

Practical experience with Master Data Management (MDM) concepts and implementation.
Define and implement master data governance processes for domains such as Customer, Product, Supplier, Location, Employee, etc.
Understand reference data, golden records, survivorship rules, matching, merging, and hierarchy management.
Work with business data owners and stewards to establish master data standards.
Support MDM integration with enterprise data platforms and downstream applications.

5. Snowflake & Modern Data Architecture

Strong understanding of Snowflake architecture and capabilities.
Good understanding of modern data architecture patterns, particularly Medallion Architecture - Bronze, Silver, and Gold layers.
Understand how data governance, metadata, lineage, DQ, security, and access controls are implemented across modern data platforms.
Working knowledge of SQL and ability to perform data analysis, profiling, validation, and DQ investigations in Snowflake.
Understand data sharing, role-based access, data security, and governance considerations within Snowflake environments.

6. Agentic AI & Emerging Technologies

Exposure to Agentic AI initiatives, AI agents, GenAI, or enterprise AI use cases.
Understand the importance of data governance, metadata, data quality, security, and responsible AI for Agentic AI solutions.
Participate in identifying and implementing governance patterns for AI-ready and AI-consumable data.
Support use cases involving intelligent data discovery, automated DQ remediation, metadata enrichment, data classification, or AI-powered governance.

7. Technical Delivery & Implementation

Take a hands-on approach to implementing governance and data management capabilities.
Translate governance requirements into technical solutions, workflows, rules, and controls.
Work closely with Data Engineers, Architects, Business Analysts, Data Stewards, Security, and Compliance teams.
Participate in solution design, configuration, development, testing, deployment, and operationalization.
Create technical and functional documentation, standards, procedures, and implementation guides.
Troubleshoot data, metadata, lineage, and quality issues and drive them through resolution.

Required Technical Skills

Area

Required Skills

Data Governance

Governance frameworks, policies, standards, guardrails, operating models

Data Catalog

Informatica, Collibra, or equivalent

Metadata

Business & technical metadata, glossary, metadata management

Data Lineage

End-to-end lineage, impact analysis, dependency mapping

Data Quality

DQ rules, profiling, scorecards, monitoring, remediation

MDM

Golden record, matching, survivorship, hierarchy, stewardship

Snowflake

Architecture, SQL, security, governance, Medallion Architecture

Data Architecture

Bronze/Silver/Gold, Data Lake/Lakehouse concepts

Agentic AI, GenAI, AI governance, AI-ready data

Technical Skills

SQL, data analysis, profiling, scripting/automation

Governance & Compliance

Data classification, privacy, regulatory controls, access governance

Preferred Skills

Informatica Data Quality / Informatica Axon / Informatica Cloud Data Governance.
Collibra Data Intelligence Platform.
Experience with Microsoft Azure / Microsoft Fabric or other modern cloud data platforms.
Experience with Power BI or other data visualization platforms.
Knowledge of Data Mesh, Data Products, Data Contracts, and domain-oriented governance.
Experience implementing governance in large enterprise environments.
Knowledge of Responsible AI and AI governance frameworks.
Experience with Agile delivery methodologies and DevOps practices.

Key Competencies

Strong analytical and problem-solving skills.
Ability to translate business requirements into practical governance solutions.
Strong stakeholder management and communication skills.
Ability to work across business and technology teams.
Strong ownership and execution mindset.
Comfortable working hands-on with data, tools, SQL, metadata, and governance platforms.
Ability to establish governance without creating unnecessary operational complexity.
Strong documentation and presentation skills.

Education

Bachelors or Masters degree in Computer Science, Information Technology, Data Management, Engineering, or a related discipline.
Relevant certifications in Data Governance, Data Management, Informatica, Collibra, Snowflake, or cloud technologies are desirable.

Expected Experience Profile

The ideal candidate should demonstrate:

7-10 years of experience in Data Management, Data Governance, Data Quality, or related data disciplines.
Proven hands-on implementation experience with at least one enterprise governance platform such as Informatica or Collibra.
Practical experience implementing catalog, metadata, lineage, DQ, and MDM capabilities.
Strong understanding of modern data platforms and Snowflake.
Exposure to Agentic AI / GenAI initiatives.
Ability to independently drive governance initiatives from requirements design implementation operationalization.