Senior technical leader for enterprise data engineering, data platform operations, and advanced analytics enablement across Databricks, Delta Lake, Apache Spark, AI/BI capabilities, and cloud data architectures.
Compensation
$133,000.00 - $148,000.00
Responsibilities
Lead the design, implementation, optimization, and operational maturity of enterprise data engineering capabilities across the Data & AI platform.
Establish engineering standards, reusable frameworks, architectural patterns, automation practices, and operational procedures that support scalable and reliable enterprise data services.
Lead development and modernization of enterprise data pipelines, Lakehouse architecture components, data products, and integration capabilities.
Guide complex migration and modernization efforts, including Redshift-to-Databricks transitions and enterprise data platform transformation initiatives.
Lead engineering efforts supporting Databricks AI/BI dashboards, Genie Agents, Genie One, semantic models, governed data products, data marts, and advanced analytics capabilities.
Requirements
Bachelor's Degree in Computer Science, Information Systems, Software Engineering, Data Science, Information Technology, Computer Engineering, or a related technical discipline or equivalent combination of education and experience.
Nice to have: Master's Degree in Computer Science, Information Systems, Software Engineering, Data Science, Information Technology, Computer Engineering, or a related technical discipline
Nice to have: 8+ years of progressive experience in enterprise data engineering, cloud data platforms, analytics engineering, AI enablement, or Lakehouse operations
Nice to have: Experience serving as a Senior Data Engineer, Lead Data Engineer, Data Platform Engineer, Analytics Engineer, or similar senior technical role
Nice to have: Experience leading enterprise data modernization, Lakehouse transformation, AI enablement, and cloud migration initiatives
Leading and scaling a world-class engineering organization of 100+ data engineers, ML engineers, and platform developers, providing strategic direction for enterprise-scale lakehouse architecture and autonomous AI systems.
Compensation
anticipated base salary range for this position is $185,000 to $265,000
Responsibilities
Lead and scale a world-class engineering organization of 100+ data engineers, ML engineers, and platform developers, including managing managers and Staff/Principal-level engineers while driving hiring, retention, and talent development strategies
Provide strategic technical direction for enterprise-scale lakehouse architecture using tools such as Databricks Data Intelligence Platform (Unity Catalog, Delta Lake, Delta Live Tables, Mosaic AI) and AWS cloud services
Drive the organization's transition to production-grade autonomous AI systems, leveraging tools such as Databricks AI stack including MLflow, Feature Store, Vector Search, and Model Serving
Establish rigorous engineering standards and operational excellence practices including SLOs, error budgets, incident management, and infrastructure-as-code using tools as Terraform and Databricks Asset Bundles
Oversee enterprise semantic modeling and RAG architecture strategies, ensuring AI systems are grounded in Unity Catalog-governed data assets with proper access controls, lineage tracking, and auditability
Lead and scale a world-class engineering organization of 100+ data engineers, ML engineers, and platform developers, including managing managers and Staff/Principal-level engineers while driving hiring, retention, and talent development strategies.
Compensation
(This section is only applicable to US candidates) S&P Global states that the anticipated base salary range for this position is $185,000 to $265,000. Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses and certifications. In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan. This role is eligible to receive additional S&P Global benefits.
Responsibilities
Lead and scale a world-class engineering organization of 100+ data engineers, ML engineers, and platform developers, including managing managers and Staff/Principal-level engineers while driving hiring, retention, and talent development strategies
Provide strategic technical direction for enterprise-scale lakehouse architecture using tools such as Databricks Data Intelligence Platform (Unity Catalog, Delta Lake, Delta Live Tables, Mosaic AI) and AWS cloud services, ensuring highly performant, cost-effective, and interoperable data foundations
Drive the organization's transition to production-grade autonomous AI systems, leveraging tools such as Databricks AI stack including MLflow, Feature Store, Vector Search, and Model Serving to deliver measurable business value beyond proof-of-concept implementations
Establish rigorous engineering standards and operational excellence practices including SLOs, error budgets, incident management, and infrastructure-as-code using tools such as Terraform and Databricks Asset Bundles for reliable platform delivery
Oversee enterprise semantic modeling and RAG architecture strategies, ensuring AI systems are grounded in Unity Catalog-governed data assets with proper access controls, lineage tracking, and auditability to prevent hallucinations
Head of Engineering - Inbound DataS&P Global · New York, US