S&P Global

13 hours ago

Head of Engineering - Inbound Data

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Lead and scale a 100+ person engineering organization focused on inbound data transformation and replacement of legacy technical debt. Own enterprise lakehouse architecture on Databricks and AWS, driving production-grade autonomous AI systems and measurable business value. Set engineering standards and operational excellence using SLOs, error budgets, incident management, and infrastructure-as-code. Oversee semantic modeling and RAG architecture with governance, lineage, and auditability while partnering with Product and FinOps.

Location: New York, Washington DC

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Sr. Director level

Key Responsibilities

•Lead and scale a world-class engineering organization (100+ engineers) including managing managers and Staff/Principal-level contributors, while driving hiring, retention, and talent development.
•Provide strategic technical direction for enterprise-scale lakehouse architecture on Databricks and AWS to deliver performant, cost-effective, interoperable data foundations.
•Drive the transition to production-grade autonomous AI systems using Databricks AI stack components (MLflow, Feature Store, Vector Search, Model Serving).
•Establish engineering standards and operational excellence practices (SLOs, error budgets, incident management) and deliver reliable platforms using infrastructure-as-code such as Terraform and Databricks Asset Bundles.
•Oversee enterprise semantic modeling and RAG architecture strategies with Unity Catalog-governed data assets, access controls, lineage tracking, and auditability to prevent hallucinations.

Pay and Benefits

Salary: USD 185,000 - 265,000 annually

Perks:Health InsurancePaid LeaveLearning Budget

Key Requirements

•15+ years of engineering experience with 5+ years directly managing and scaling large engineering teams at Director or Head of Engineering level, including experience managing managers and transforming Staff/Principal engineers.
•Deep expertise in Databricks Data Intelligence Platform (Unity Catalog, Delta Lake internals, Delta Live Tables, Databricks Workflows, MLflow, Mosaic AI) with the ability to guide complex platform trade-offs.
•Extensive experience architecting enterprise-scale data platforms on AWS, including Amazon S3, AWS Glue, Amazon EMR, AWS Lake Formation, multi-region deployment strategies, and security patterns (IAM, VPC, KMS).
•Proven technical depth in Apache Iceberg internals, schema evolution, and cross-platform table strategies, plus hands-on experience deploying autonomous AI and production RAG pipelines.
•Demonstrated ability to build and scale engineering organizations (20+ to 100+ engineers) while establishing engineering standards, agile delivery practices, and operational SLAs for data and AI products.

Experience:15+ yearsData engineeringMachine learningCloudAutonomous AI

Skills:LeadershipCommunicationOrganizational transformationStrategic technical guidanceCollaboration

Certifications:AWS certificationDatabricks certification

Tech Stack:DatabricksDatabricks Data Intelligence PlatformUnity CatalogDelta LakeDelta Live TablesDatabricks WorkflowsMLflowMosaic AIAWSAmazon S3AWS GlueAmazon EMRAWS Lake FormationIAMVPCKMSApache IcebergRAGTerraformDatabricks Asset Bundles

Company Brief

S&P Global

Provides financial information, analytics, benchmarks, and credit ratings to markets and institutions worldwide, offering data, research, indices, and risk assessment tools across the financial services and commodities sectors.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 1917

Website LinkedIn

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S&P Global

13 hours ago

Head of Engineering - Inbound Data

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Location: New York, Washington DC

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Sr. Director level

Key Responsibilities

•Lead and scale a world-class engineering organization (100+ engineers) including managing managers and Staff/Principal-level contributors, while driving hiring, retention, and talent development.
•Provide strategic technical direction for enterprise-scale lakehouse architecture on Databricks and AWS to deliver performant, cost-effective, interoperable data foundations.
•Drive the transition to production-grade autonomous AI systems using Databricks AI stack components (MLflow, Feature Store, Vector Search, Model Serving).
•Establish engineering standards and operational excellence practices (SLOs, error budgets, incident management) and deliver reliable platforms using infrastructure-as-code such as Terraform and Databricks Asset Bundles.
•Oversee enterprise semantic modeling and RAG architecture strategies with Unity Catalog-governed data assets, access controls, lineage tracking, and auditability to prevent hallucinations.

Pay and Benefits

Salary: USD 185,000 - 265,000 annually

Perks:Health InsurancePaid LeaveLearning Budget

Key Requirements

•15+ years of engineering experience with 5+ years directly managing and scaling large engineering teams at Director or Head of Engineering level, including experience managing managers and transforming Staff/Principal engineers.
•Deep expertise in Databricks Data Intelligence Platform (Unity Catalog, Delta Lake internals, Delta Live Tables, Databricks Workflows, MLflow, Mosaic AI) with the ability to guide complex platform trade-offs.
•Extensive experience architecting enterprise-scale data platforms on AWS, including Amazon S3, AWS Glue, Amazon EMR, AWS Lake Formation, multi-region deployment strategies, and security patterns (IAM, VPC, KMS).
•Proven technical depth in Apache Iceberg internals, schema evolution, and cross-platform table strategies, plus hands-on experience deploying autonomous AI and production RAG pipelines.
•Demonstrated ability to build and scale engineering organizations (20+ to 100+ engineers) while establishing engineering standards, agile delivery practices, and operational SLAs for data and AI products.

Experience:15+ yearsData engineeringMachine learningCloudAutonomous AI

Skills:LeadershipCommunicationOrganizational transformationStrategic technical guidanceCollaboration

Certifications:AWS certificationDatabricks certification

Company Brief

S&P Global

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 1917

Website LinkedIn