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 consumption. Partner with engineering, data science, and business collabor...