EY - GDS Consulting - AI And DATA - Informatica CDGC - Manager

Objectives and Purpose

The Data Quality Manager is responsible for driving enterprise-wide data quality and governance initiatives using Informatica Intelligent Data Management Cloud (IDMC), including Cloud Data Quality (CDQ), Cloud Data Governance & Catalog (CDGC), and related components.

The role ensures high levels of data accuracy, completeness, and consistency across platforms by implementing data quality strategies, leading engineering teams, and partnering with governance stakeholders to embed DQ controls into the data ecosystem.

Key Accountabilities

• Data Quality Strategy & Execution
  • Design and implement cloud-based data profiling frameworks to assess data health across critical datasets (distinct counts, nulls, outliers, patterns, etc.).
  • Develop and maintain data quality rules and specifications for validity, completeness, conformity, and integrity; enable parameterization and reuse across domains.
  • Implement exception management workflows, automate notifications, and coordinate remediation with data stewards.
  • Create and manage cleansing and standardization assets, including parsing, casing, dictionary lookups, address validation, and matching.
  • Build and publish scorecards to monitor KPIs, thresholds, and trends; socialize findings with business and product stakeholders.
  • Define Critical Data Elements (CDEs) in collaboration with data stewards and align thresholds with governance standards.
  • Manage reference data and code lists using Reference 360.
• Data Governance & Metadata Management
  • Configure and operate CDGC and Metadata Command Centre (MCC) for metadata scans, lineage mapping, glossary curation, and asset classification.
  • Link DQ scorecards to governed assets to ensure traceability and transparency across the data lifecycle.
  • Expose end-to-end lineage from source to consumption layers, supporting governance and compliance initiatives.
• Data Engineering & Automation
  • Lead the design, optimization, and maintenance of data pipelines and integration frameworks aligned with enterprise ETL and data governance principles.
  • Embed DQ validation checkpoints within CDI mappings and taskflows to ensure continuous data quality enforcement.
  • Leverage IICS REST APIs and Python for orchestration, automation, and post-processing of exception extracts.
  • Implement Cloud API integration patterns (OAuth, throttling, managed API consumption) to trigger and monitor DQ flows programmatically.
  • Support deployment automation, migration, and operational enablement across environments.
• Technical Leadership & Collaboration
  • Collaborate with enterprise architects, data scientists, and visualization teams to enable advanced analytics, machine learning, and predictive modelling.
  • Mentor and guide technical teams in DQ best practices, performance optimization, and cloud enablement.
  • Promote reusability, standardization, and a culture of continuous improvement across data engineering and governance functions.
  • Partner with data governance councils to align DQ frameworks with enterprise data policies.

Required Qualifications & Experience

•       Bachelor’s degree in computer science, Engineering, or Data Science.

•       10+ years of experience in Data Quality, Data Governance, or Data Engineering roles.

•       Proven expertise in:

• Informatica IICS / IDMC – Cloud Data Quality, Cloud Data Integration, CDGC, MCC, and Data Marketplace.

• • • Cloud Data Profiling, Rule Specifications, Exception Tasks, Scorecards, and Cleanse Assets.
    • CDGC configuration – metadata cataloguing, lineage, glossary, and DQ linkage.
    • Reference 360 – code lists, crosswalks, lifecycle management.
    • CDI mappings & taskflows, parameterization, and dependency orchestration.
    • Cloud APIs and automation scripting (Python, REST APIs).
    • Cloud platforms (AWS / Azure), Databricks, Spark, and modern data architecture (Mesh, Fabric).
    • Data modelling, relational databases, and CI/CD using GitHub / GitLab.

Preferred Skills

•       Master’s degree in data or computer science.

•       Certifications: Databricks Certified Data Engineer Professional, AWS Certified Data Engineer – Associate.

•       Experience with IDMC MDM SaaS, Data Marketplace, and Unity Catalog for governance and access control.

•       Familiarity with data privacy and compliance frameworks (GDPR, HIPAA, etc.).

•       Exposure to pharma or life sciences domain preferred.

•       Knowledge of Snowflake, Redshift, Postgres, and NoSQL data platforms.

•       Experience with Airflow / Tidal orchestration tools.

•       Proficiency in SQL and data analysis.

Key Attributes

•       Strong problem-solving, analytical, and decision-making skills.

•       Excellent communication and stakeholder management across business and technology teams.

•       Proven leadership in managing distributed teams and driving data quality initiatives.

•       Ability to operate in fast-paced environments and manage multiple priorities effectively.

•       Commitment to continuous learning, innovation, and cloud modernization.