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S&P Global

Delivers credit ratings, market data, indices

Head of Engineering - Inbound Data

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 15 years of engineering experience, including at least 5 years directly managing and scaling large engineering teams at Director or Head of Engineering level, including managing managers and guiding Staff/Principal-level individual contributors through organizational transformation.
  • Deep expertise in the Databricks Data Intelligence Platform, including Unity Catalog, Delta Lake internals, Delta Live Tables, Databricks Workflows, MLflow, and Mosaic AI, with the ability to engage in technical discussions and provide strategic guidance on complex platform trade-offs.
  • Extensive experience architecting enterprise-scale data platforms on AWS, including Amazon S3, AWS Glue, Amazon EMR, and AWS Lake Formation, with a strong understanding of multi-region deployment strategies and security patterns such as IAM, VPC, and KMS.
  • Proven technical depth in Apache Iceberg internals, schema evolution, and cross-platform table strategies, combined with hands-on experience deploying autonomous AI agents and architecting RAG pipelines for production environments.
  • Demonstrated ability to build and scale engineering organizations from 20+ to 100+ engineers while establishing rigorous engineering standards, agile delivery practices, and operational SLAs for complex data and AI products.
  • Experience translating complex technical trade-offs to non-technical stakeholders and influencing executive decision-making through data-driven recommendations and ROI analysis.
  • Strong leadership and communication skills.
  • AWS and/or Databricks certifications, and experience partnering with FinOps and cloud platform teams to optimize cloud consumption, performance, and platform ROI across multi-cloud data platform strategies.

Responsibilities

  • Lead and scale a 100+ person engineering organization of data engineers, ML engineers, and platform developers, including managing managers and Staff/Principal-level engineers, and driving hiring, retention, and talent development strategies.
  • Provide strategic technical direction for enterprise-scale lakehouse architecture using the Databricks Data Intelligence Platform and AWS cloud services, ensuring highly performant, cost-effective, and interoperable data foundations.
  • Drive the organization's transition to production-grade autonomous AI systems using the Databricks AI stack, including MLflow, Feature Store, Vector Search, and Model Serving, to deliver measurable business value beyond proof-of-concept implementations.
  • Establish engineering standards and operational excellence practices, including SLOs, error budgets, incident management, and infrastructure-as-code using 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 appropriate access controls, lineage tracking, and auditability to prevent hallucinations.
  • Foster an engineering culture rooted in psychological safety, continuous learning, and rapid experimentation while partnering with Product, FinOps, and executive leadership to translate business goals into actionable technical roadmaps.

Desired Qualifications

  • Experience with semantic modeling, knowledge graphs, and enterprise data governance frameworks, including metadata management and secure data sharing patterns at enterprise scale.
  • Background in LLMOps, model evaluation, and prompt orchestration, with familiarity integrating AWS AI/ML services such as Amazon SageMaker and Amazon Bedrock into broader enterprise AI platform strategies.
  • Experience with infrastructure-as-code tools such as Terraform, CI/CD pipelines, and deployment automation, including Databricks Asset Bundles for repeatable, auditable platform delivery across distributed cloud environments.

About the Company

S&P Global

Delivers credit ratings, market data, indices

S&P Global provides financial information and analytics for investors, corporations, and governments, including credit ratings, market data, and indices. It compiles large financial data, conducts research, and offers analytics, ratings, and benchmarks accessed via subscriptions, licenses, or transaction-based services. The company differentiates itself with an integrated suite that covers ratings, data, analytics, indices, and ESG solutions across global markets, backed by well-known brands. Its goal is to help clients make informed decisions, manage risk, and drive growth while prioritizing corporate responsibility.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1917

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