Data Engineer, Data Platforms

About the Role: Grade Level (for internal use): 10 Key Responsibilities Data Pipeline Transition and Platform Delivery

• Partner with Databricks and platform teams to transition existing pipelines into the target enterprise data platform.
• Provide hands-on engineering support to stabilize and optimize pipelines post-transition, focusing on performance, scalability, maintainability, and operational reliability.
• Implement and follow repeatable engineering patterns for ingestion, transformation, testing, deployment, and monitoring.
• Support secure AWS deployment patterns and governed data access using AWS IAM, encryption, and platform guardrails.
• Work with lakehouse technologies such as Delta Lake, Apache Iceberg, and Databricks Unity Catalog, and support metadata-driven pipeline design.
• Assist with establishing and maintaining observability practices (logging, telemetry, alerts, dashboards) for production pipelines. Data Onboarding and Asset-Agnostic Enablement
• Support asset-agnostic onboarding by applying standard ingestion and transformation frameworks to new datasets.
• Help offshore teams adopt common onboarding standards, delivery practices, and technical templates.
• Contribute to reusable technical assets such as reference implementations, onboarding templates, documentation, and operational runbooks.
• Support both batch and streaming onboarding patterns using AWS services (e.g., AWS Glue, AWS Lambda, Amazon Kinesis) or event-driven integrations as appropriate. Data Mastering Platform Integration
• Support integration of platform datasets with the enterprise data mastering platform.
• Help establish and/or maintain data quality controls, reconciliation, and metadata alignment for trusted mastered data.
• Support golden record / golden copy generation and maintenance activities for key financial datasets (as applicable to the program). Technical Leadership and Engineering Excellence
• Provide technical guidance to engineering peers through code reviews, design reviews, and implementation planning.
• Contribute to engineering standards and delivery rigor across CI/CD, infrastructure automation, testing practices, and operational readiness.
• Help ensure documentation quality and operational discipline (runbooks, support procedures, incident learnings).
• Act as a technical bridge between offshore execution teams and global platform stakeholders to resolve delivery blockers and keep alignment. AI-Assisted Engineering and Context Engineering
• Use AI tools (Claude, GitHub CoPilot, LLMs) to accelerate engineering tasks such as drafting code, refactoring, writing documentation, generating unit tests, and troubleshooting.
• Apply basic prompt engineering and context engineering practices by providing the right technical background, constraints, schemas, examples, and acceptance criteria to improve output quality.
• Validate and verify AI-generated outputs before adoption, especially for correctness, security, and maintainability.
• Follow responsible AI usage expectations, including protection of sensitive data, credentials, and regulated information. Required Qualifications Technical Experience
• 5–7+ years of experience in data engineering, data platforms, or related technical domains.
• Hands-on experience building and operating batch and/or streaming data pipelines.
• Experience working with Databricks-based platforms and lakehouse architectures.
• Strong familiarity with AWS data engineering services such as Amazon S3, AWS Glue, AWS Lambda, AWS Lake Formation, Amazon Kinesis, and

AWS Iam.

• Working knowledge of Delta Lake, Apache Iceberg, and Databricks Unity Catalog (or equivalent governed lakehouse concepts).
• Solid understanding of data quality, schema management, lineage/metadata basics, access control, encryption, and operational support. Leadership and Collaboration
• Ability to provide technical guidance without people management responsibility.
• Experience collaborating with global teams across time zones and working through ambiguous delivery problems.
• Strong communication skills and ability to translate technical requirements into implementable tasks. AI Tooling (Required)
• Practical experience using AI-assisted engineering tools such as Claude, GitHub CoPilot, or LLM-based development features.
• Ability to use AI effectively with basic context engineering practices (inputs/constraints/examples/acceptance criteria).
• Demonstrated ability to validate AI-generated outputs and follow responsible, secure usage practices. Preferred Qualifications
• Experience with enterprise onboarding frameworks, reusable ingestion patterns, and pipeline templates.
• Familiarity with data cataloging/metadata management and governed data product concepts.
• Knowledge of semantic modeling (e.g., semantic layers, business definitions, canonical models) is a plus.
• Exposure to enterprise data mastering/MDM workflows, golden record concepts, and trusted data distribution.
• Experience in regulated environments with strong governance, auditability, and security expectations.
• Databricks and/or AWS certifications (or equivalent practical experience) are a plus. About S&P Global Dow Jones Indic e s At S&P Dow Jones Indices, we provide iconic and innovative index solutions backed by unparalleled expertise across the asset-class spectrum. By bringing transparency to the global capital markets, we empower investors everywhere to make decisions with conviction. We’re the largest global resource for index-based concepts, data and research, and home to iconic financial market indicators, such as the S&P 500 ® and the Dow Jones Industrial Average ® . More assets are invested in products based upon our indices than any other index provider in the world. With over USD 7.4 trillion in passively managed assets linked to our indices and over USD 11.3 trillion benchmarked to our indices, our solutions are widely considered indispensable in tracking market performance, evaluating portfolios and developing investment strategies. S&P Dow Jones Indices is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today. For more information, visit www.spglobal.com/spdji . What’s In It For You? Our Mission: Advancing Essential Intelligence. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include:
• Health & Wellness: Health care coverage designed for the mind and body.
• Flexible