Senior Manager Enterprise Data, Analytics & AI

Key Responsibilities

• Data Platform & Engineering Architect, build, and operate a scalable enterprise data platform (cloud-native).
• Own the full data lifecycle: ingestion, transformation, storage, orchestration, and consumption layers.
• Establish and enforce data quality frameworks, SLA monitoring, and lineage tracking.
• Drive adoption of modern data stack tooling (dbt, Airflow, Spark, Kafka, Databricks, Snowflake, etc.).
• AI & Machine Learning - Define and execute the enterprise AI/ML roadmap in collaboration with business stakeholders.
• Oversee the design, development, deployment, and monitoring of production AI/ML models.
• Evaluate and integrate large language models (LLMs) and generative AI capabilities into business workflows.
• Implement MLOps best practices including CI/CD for models.
• Analytics & Business Intelligence - Lead the development of self-service analytics capabilities, semantic layers, and BI infrastructure.
• Define KPIs, metrics frameworks, and executive reporting cadences.
• Championing a data-literate culture by delivering training, documentation, and stakeholder enablement.

Experience Required

• 8+ years in data engineering, analytics, or ML roles.
• 3+ years leading technical data teams.
• Hands-on experience ML or AI systems.
• Track record of building enterprise-grade data platforms.

Technical Skills

• Expert-level SQL and Python.
• Cloud platforms: Azure.
• Data warehousing: Databricks or equivalent.
• ML frameworks.

Benefits

Competitive compensation
Comprehensive benefits package
A diverse array of resources to support you professionally and personally.