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Job Description
Structured overview of role & requirementsAbout This Role
Lead enterprise-wide Data Quality strategy, architecture, and adoption of scalable frameworks and platforms across batch, streaming, cloud, on-premises, and SaaS environments.
Develop reusable metadata-driven data quality capabilities including rule management, observability, profiling, anomaly detection, and remediation workflows with measurable KPIs.
Drive Data Quality as Code, automation, AI/ML integration, and enterprise governance partnerships to improve data trust, operational efficiency, and platform reliability.
Minimum Requirements
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related discipline.
10+ years experience in Data Engineering, Data Platforms, or Data Architecture.
5+ years leading enterprise-scale data quality, observability, or data reliability initiatives.
Proficiency with SQL, Python, Spark/PySpark; experience with Streaming technologies and Cloud data platforms.
Ideal Candidate Profile
Experienced in designing and governing data quality platforms integrating metadata management, lineage, master data management, and data observability.
Ability to lead and influence cross-functional teams including Data Governance, Security, Compliance, Analytics, AI, and business stakeholders.
Capability to leverage AI/ML and Generative AI technologies to automate data quality monitoring, root cause analysis, and enhance engineering productivity.