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Location
Hybrid (Hyderabad, India)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 14, 2026. Cognizant scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Cognizant is an American information technology services and consulting company founded in 1994 as an in-house technology unit of Dun and Bradstreet in Chennai, India, and headquartered in Teaneck, New Jersey. It builds, integrates and operates software and infrastructure for large enterprises, with particularly deep positions in healthcare, financial services, insurance and life sciences, delivered by a global workforce of more than three hundred thousand people concentrated in India. Listed on Nasdaq, the company competes with the large Indian and global systems integrators and has reoriented its offerings around cloud migration, data platforms and AI-assisted engineering.

Job Summary

This hybrid day shift role focuses on establishing robust AI driven data governance and lineage practices for enterprise data platforms using warehouse technologies Databricks and Informatica tools. The specialist will design and operationalize frameworks that ensure trusted data regulatory compliance and high quality information flow across business functions supporting transparent decision making and enabling sustainable value creation for clients and society through responsible data use.

Responsibilities

  • Design and implement comprehensive data governance frameworks across data warehouse and Databricks platforms to ensure consistent standards policies and controls that enable trusted analytics and responsible data driven decisions across the organization.
  • Define and maintain detailed data lineage models by configuring and optimizing Informatica EDC and CDGC tools to provide end to end visibility of data flows transformations and usage patterns for regulatory reporting and impact analysis.
  • Configure and administer Collibra environments to establish an enterprise data catalog business glossary and stewardship workflows that simplify data discovery ownership clarity and collaboration among technical and business stakeholders.
  • Develop and maintain Axon and HC Data Management solutions to capture data governance metadata critical data element definitions and data quality rules that support consistent data usage and reduce operational risks in downstream applications.
  • Collaborate with data engineering teams working on Databricks and data warehouse pipelines to embed governance controls metadata capture and lineage tracking mechanisms directly into ingestion and transformation processes.
  • Create and refine standards for data quality monitoring using Informatica tooling to proactively identify anomalies measure data health and drive remediation actions that protect reporting accuracy and customer outcomes.
  • Engage with business partners including asset management operations stakeholders when relevant to translate regulatory compliance and operational requirements into practical data governance controls and lineage documentation.
  • Develop clear procedures playbooks and guidance documents that explain data governance processes stewardship responsibilities and usage protocols in language accessible to both business and technical teams.
  • Coordinate periodic assessments and audits of data governance and lineage implementations to verify adherence to policy identify gaps and recommend prioritized improvements that enhance resilience and transparency.
  • Drive integration of Collibra Axon EDC and CDGC metadata repositories with data warehouse and Databricks infrastructures to maintain a single reliable view of data assets ownership quality and lineage across the enterprise.
  • Support incident analysis and root cause investigations by leveraging detailed lineage views to trace data issues back to specific sources transformations or controls thereby reducing resolution time and preventing recurrence.
  • Provide guidance and enablement to project teams on best practices for metadata management tagging standards and stewardship models so that new solutions align with enterprise data governance expectations from inception.
  • Contribute to the evolution of data governance strategies by monitoring industry trends regulatory changes and emerging AI data management practices ensuring that the organization remains compliant ethical and competitive in its use of data.

Qualifications

  • Demonstrate deep hands on experience in designing and operating enterprise data warehouses combined with strong Databricks skills to support scalable data engineering and analytics aligned with governance requirements.
  • Show advanced proficiency with Informatica platforms including HC Data Management core Informatica services Axon EDC and CDGC for implementing metadata management data quality and governance solutions in complex environments.
  • Apply practical expertise in Collibra configuration and administration to build sustainable data catalogs glossaries and stewardship workflows that enhance data literacy and accountability across teams.
  • Exhibit strong understanding of data governance principles data lineage modeling and regulatory expectations ideally complemented by exposure to asset management operations or similar data intensive financial domains.
  • Utilize effective communication and stakeholder engagement capabilities to explain data governance concepts negotiate priorities and align diverse technical and business groups around shared data standards without relying on formal leadership authority.
  • Leverage analytical and problem solving strengths to diagnose data quality or lineage issues design targeted remediation initiatives and demonstrate measurable improvements in data reliability and decision support outcomes.

Certifications Required

Preferred certifications include Informatica Data Governance or Data Quality certification and Collibra Ranger or similar data governance credential.

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