Director, Software Engineering
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Job Description
Director leading Databricks pipeline migration, AI-assisted engineering, and data mastering integration. Driving enterprise data-platform delivery for S&P Global’s global financial intelligence business.
Responsibilities:
- Partner with the core Databricks team to plan and execute transition of existing data pipelines to the target enterprise data platform
- Implement repeatable engineering patterns for ingestion, transformation, testing, deployment, and monitoring across onboarded datasets
- Lead adoption of AI-powered development tools such as Claude, GitHub CoPilot, and LLMs
- Develop context engineering practices and reusable context packs
- Guide offshore teams in defining and operationalizing asset-agnostic onboarding patterns for data assets, domains, and source systems
- Establish reusable ingestion and processing patterns for batch and streaming use cases
- Integrate platform pipelines and datasets with the enterprise data mastering platform
- Establish data quality controls, reconciliation processes, and metadata alignment
- Support consistent business definitions, reusable data concepts, and governed consumption patterns
- Provide senior technical guidance for offshore data platform engineering
- Influence architectural decisions and contribute to design and code reviews for complex data platform initiatives
- Collaborate with global platform, architecture, governance, security, data mastering, Databricks-aligned, partner, offshore, and upstream/downstream teams
Requirements:
- 10+ years of experience in data engineering, data platforms, cloud data architecture, software engineering, or related engineering domains
- Experience as a senior Individual Contributor, technical lead, principal engineer, staff engineer, distinguished engineer, architect, or equivalent in complex data platform environments
- Strong hands-on experience with modern data engineering and pipeline development
- Experience with batch and/or streaming data workflows
- Experience with Databricks-based data platforms and lakehouse-oriented architectures
- Practical experience using AI-assisted engineering tools such as Claude, GitHub CoPilot, LLMs, or similar
- Experience applying LLMs to engineering use cases such as code generation and optimization
- External candidates reaching the final interview stage must attend at least one in-person interview at the nearest S&P Global office
- Familiarity with enterprise data cataloging, metadata management, business glossary, lineage, operational metadata platforms, or semantic data layers
- Experience with NeoXam DataHub or NeoXam-style mastering workflows
- Knowledge of semantic modeling
- Strong leadership skills, including coaching, empowering others, and building consensus across groups
Benefits:
- Annual incentive plan eligibility
- Health care coverage
- Generous time off
- Continuous learning and career development resources
- Competitive pay
- Retirement planning
- Continuing education program with company-matched student loan contribution
- Financial wellness programs
- Family benefits and perks
- Retail discounts
- Referral incentive awards
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