Senior AI Engineer Manager

About the role

This role owns platform operations, integration, observability, monitoring, data quality, lineage, cataloging, security, and engineering enablement across Databricks, Snowflake, and Azure-based data platforms. The leader will deliver a secure, scalable, reliable, and cost-efficient foundation for ingestion, ETL/ELT, orchestration, governance, semantic and ontology capabilities, and production support across enterprise domains.

What you'll do

• Lead the enterprise data engineering platform operating model across Databricks, Snowflake, Azure Data Lake, ingestion, transformation, orchestration, governance
• Own platform administration, including workspaces, clusters, SQL warehouses, Unity Catalog, Snowflake roles, resource monitors, workload isolation
• Define observability and monitoring standards for pipelines, workflows, compute, storage, integrations, data freshness, data quality, lineage, performance, reliability
• Drive automation through self-service provisioning, reusable templates, CI/CD, testing frameworks, release automation, and Infrastructure-as-Code
• Define integration patterns across Databricks, Snowflake, Azure Data Factory, dbt, Kafka/Event Hubs, APIs, enterprise applications, databases, file sources, BI tools

What you need

• 10–18 yrs of experience
• SQL
• ETL
• Databricks
• Snowflake
• Azure Data Factory
• dbt
• Any graduate

Good to have

• AWS
• GCP
• MLOps
• Spark
• Kafka
• Airflow