EY Customer-Insights & Analytics Primary market research -Manager 

India, Karnataka, Bengaluru 

268137437

Objectives and Purpose

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

• Data Quality Strategy & Execution
  • Design and implementcloud-based data profilingframeworks to assess data health across critical datasets (distinct counts, nulls, outliers, patterns, etc.).
  • Develop and maintaindata quality rules and specificationsfor validity, completeness, conformity, and integrity; enable parameterization and reuse across domains.
  • Implementexception management workflows, automate notifications, and coordinate remediation with data stewards.
  • Create and managecleansing and standardizationassets, including parsing, casing, dictionary lookups, address validation, and matching.
  • Build and publishscorecardsto 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.
  • Managereferencedataand code lists usingReference 360.
• Data Governance & Metadata Management
  • Configure and operateCDGC and Metadata Command Centre (MCC)for metadata scans, lineage mapping, glossary curation, and asset classification.
  • LinkDQ scorecards to governed assetsto ensure traceability and transparency across the data lifecycle.
  • Exposeend-to-end lineagefrom source to consumption layers, supporting governance and compliance initiatives.
• Data Engineering & Automation
  • Lead the design, optimization, and maintenance ofdata pipelines and integration frameworksaligned with enterprise ETL and data governance principles.
  • EmbedDQ validation checkpointswithinCDI mappings and taskflowsto ensure continuous data quality enforcement.
  • LeverageIICS REST APIsandPythonfor orchestration, automation, and post-processing of exception extracts.
  • ImplementCloud API integration patterns(OAuth, throttling, managed API consumption) to trigger and monitor DQ flows programmatically.
  • Supportdeployment 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.

Bachelor’s degreein computer science, Engineering, or Data Science.

Data Quality, Data Governance, or Data Engineering

• 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 APIsand automation scripting (Python, REST APIs).
    • Cloud platforms(AWS / Azure),Databricks,Spark, andmodern data architecture(Mesh, Fabric).
    • Data modelling, relational databases, and CI/CD using GitHub / GitLab.

Master’s degreein data or computer science.

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

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

• Familiarity with(GDPR, HIPAA, etc.).

• Exposure topharma or life sciences domain

• Knowledge ofSnowflake, Redshift, Postgres, and NoSQLdata platforms.

• Experience with
orchestration tools.

• Proficiency in SQL and data analysis.

• 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.