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.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
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