Position Responsibilities

• Design and implement data integration solutions to facilitate seamless data flow between systems.
• Architect and oversee data ingestion, transformation, and orchestration using ADF/Synapse pipelines, Databricks Workflows, and event‑based patterns.
• Establish data modeling standards (dimensional/Kimball, Data Vault, lakehouse models) and semantic layers for BI/ML consumption.
• Implement governance: data catalogs/lineage, DQ frameworks, security, RBAC/ABAC, and compliance alignment (e.g., Purview, Unity Catalog).
• Design scalable ML platforms: feature stores, model training/serving, experiment tracking (MLflow), and CI/CD for ML (MLOps).
• Optimize performance and cost: cluster sizing, autoscaling, storage layout (partitioning/Z‑ordering), caching, and query tuning (Spark SQL/PySpark).
• Define data contracts/APIs and integration patterns for cross‑domain interoperability and application consumpti...