Our client is seeking a Senior Data & Analytics Architect to design and scale its next-generation cloud-native data, analytics, and AI platform. This is a role with high technical ownership, influence, and the ability to shape long-term architecture decisions.
Description:
Modern Data & Lakehouse Architecture:
Design and implement scalable Lakehouse frameworks using Databricks, Delta Lake, Spark, and cloud services.
Build robust data pipelines and establish enterprise-grade standards for data governance, cataloging, lineage, and access control.
Support both real-time and batch analytics.
Machine Learning & Generative AI Enablement:
Partner with Data Science teams to operationalize ML and GenAI models.
Architect solutions for LLM fine-tuning, model deployment, and model serving, ensuring scalability and compliance.
Manage model lifecycle, feature stores, registries, and ML observability using MLflow and cloud-native tools.
MLOps & Platform Engineering:
Build and maintain CI/CD pipelines (Azure DevOps, GitHub Actions, or similar) for data/ML workflows.
Automate data transformations and orchestration pipelines.
Optimize compute infrastructure and implement observability frameworks and drift detection.
Skills & Experience:
10+ years in data architecture, data engineering, or analytics engineering.
Expertise in Databricks (pipelines, SQL, structured streaming, workflows), Spark/PySpark, and cloud data/ML services (Azure and/or AWS).
Experience with Unity Catalog, MLflow, and data governance frameworks.
Strong understanding of Lakehouse architecture, distributed compute, and modern MLOps.
Benefits:
Health & dental benefits (effective Day 1), Health Spending Account (HSA), and Wellness Spending Account (WSA).
Focus Friday afternoons.
Resources supporting mental, physical, and financial wellbeing.
Retirement / Pension plan.
Unlimited access to LinkedIn Learning and Education Assistance Program.
