- At least 10+ years of experience in enterprise data architecture, including design and implementation of large-scale data platforms and 5+ years of relevant data engineering experience on Databricks.
- Strong expertise in: Databricks (Workspace, Clusters, Jobs, Repos, Delta Live Tables)
- Deep hands-on expertise with Azure Databricks, PySpark, Delta Lake, Unity catalog, MLflow, DBT, and associated Azure data services (Data Lake, SQL, Synapse, ADF).
- Proven experience migrating from legacy data warehouse and reporting systems to modern cloud platforms.
- Experience in data modeling, data warehousing (OLTP, OLAP), security, governance, DevOps, and MLOps.
- Hands-on with CI/CD, version control (Git), and DevOps practices for data engineering
- Excellent communication, collaboration, problem-solving and analytical skills with the ability to collaborate effectively with cross-functional teams and influence decision-making at all levels of the organization.
- Ability to mentor and coach junior architects, engineers, and BI/reporting developers.
- Architect-level certifications in Databricks and DBT are preferred.
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