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Tier-1 employer and mid-level data role increases applicants, but niche Collibra/Databricks skills moderately reduce competition.
Core data engineering and governance skills transfer across industries, though Collibra/governance specifics somewhat limit portability.
Explicit 5–8 years plus required Databricks and Collibra/governance expertise creates strict filtering.
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Own the engineering and maintenance of enterprise-grade data pipelines supporting Platinum-level certified data products, ensuring performance, availability, and resilience.
Implement and maintain end-to-end technical data lineage and integrate data products with enterprise data governance platforms (e.g., Collibra) to automate lineage, metadata publishing, and observability.
Design and operationalize automated data observability controls including freshness, volume, anomaly detection, and reliability reporting, integrating outputs into governance tools for auditability and transparency.
5–8 years of experience in data engineering or analytics engineering roles.
Strong hands-on experience with Databricks and modern lakehouse architectures.
Proven experience building enterprise-grade data pipelines and integrations, including technical lineage, metadata publishing, and integration with data governance tools (preferably Collibra).
Ability to work effectively in cross-functional, matrixed environments with Data Operations, governance, and analytics teams.
Experienced in engineering integrations between data platforms and enterprise data governance solutions within regulated or compliance-driven environments.
Proficient in supporting certified, Platinum or Tier-0 enterprise data products showing operational rigor and governance awareness.
Comfortable working in product-oriented or DataOps environments emphasizing cross-team collaboration and scalable, automated data foundation engineering.