· Define reference architectures (lakehouse, warehouse, streaming/event‑driven) and lead adoption across domains.
· Architect scalable cloud data platforms on Azure (ADLS, ADF/Fabric pipelines, Databricks, Synapse; Purview for governance).
· Establish data product and data contract standards; promote domain‑oriented designs (mesh where appropriate).
· Embed security, privacy, lineage, quality, and FinOps (cost/perf) into designs.
· Partner with analytics leaders to design and govern enterprise semantic models and metric definitions; ensure optimal support for Power BI and the enterprise metrics layer.
· Enable AI/ML foundations (feature stores, ML/data pipelines, vector stores/RAG patterns) with robust MLOps and governance.
· Lead architecture reviews, mentor engineering teams, and ensure delivery adheres to guardrails.
Required Experience
· 10+ years in enterprise data architecture/solutions architecture; proven delivery at scale in regulated environments.
· Deep expertise with Azure + Databricks (Delta Lake/Unity Catalog, streaming, governance); Snowflake experience valued.
· Strong data modeling (dimensional, Data Vault, lakehouse) and data product/contract practices.
· Hands‑on design of batch + streaming pipelines; metadata/lineage, data quality frameworks.
· Demonstrated leadership influencing senior stakeholders and guiding cross‑functional teams.
· Technical Skills
o Platforms: Azure (ADLS, ADF/Fabric, Synapse, Purview), Databricks, Snowflake.
o Analytics & Semantic Layer: Power BI (enterprise modeling, semantic layer/metrics layer design, performance optimization, governance).
o Programming & IaC: SQL, Python/Scala; Terraform/ARM/Bicep.
o Streaming: Kafka/Event Hubs, Spark Structured Streaming.
o Governance & Observability: Catalog/lineage, data quality expectations, cost/perf tuning.
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