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Strong brand and metro location raise competition, while senior, niche data-architecture focus reduces applicant pool.
High because specialized data architecture, governance, and Databricks expertise limits cross-industry transferability.
High due to mandatory Databricks, data governance, MDM, and enterprise architecture skill requirements.
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Define and implement enterprise data architecture and governance using Databricks Lakehouse across Azure, AWS, or GCP platforms.
Design and maintain scalable data models and enforce data governance policies including data quality, metadata, lineage, and privacy.
Lead enterprise data solutions architecture, govern data platforms, and mentor teams on data governance and Lakehouse architecture patterns.
Experience with Databricks, Delta Lake, Unity Catalog, and cloud platforms (Azure, AWS, or GCP).
Proven expertise in data modelling techniques including dimensional modelling, Data Vault, and normalized structures.
Skilled in implementing data governance frameworks covering data quality, metadata management, and compliance.
Work Experience Required: Not explicitly mentioned in the JD.
Strong background in enterprise data architecture with hands-on experience on Databricks and Lakehouse technologies.
Familiarity with managing Master Data Management, data catalogs, and governance tools like Microsoft Purview or Collibra.
Experienced in collaborating across data engineering, analytics, and business teams to establish governed, reusable data assets.