S&P Global

The Role: Content Marketing Manager - Mobility Locations US - NY - VIRTUAL Full time Job requisition id 111 The Role: Content Marketing Manager - Mobility The Team: We are seeking a Content Marketing and Social Media Manager to join our growing marketing team and take ownership of Mobility’s campaign content, including thought leadership, organic and paid social. This role is hands-on, with an immediate focus on supporting content development for our new website and by producing clear, on-brand copy for digital experiences. Over time, the position will grow to include being the lead author for our North America sales solutions thought leadership – showcasing our expertise while driving lead generation. The right candidate will be capable of owning the content process from end-to-end: Developing new ideas (whitepapers, eBooks, articles, social media), interviewing subject matter experts and gathering data, drafting the content, spearheading stakeholder review and publication, and supporting effective digital promotion strategies. This role reports to the Associate Director of Content Strategy and complements the Digital Content & SEO Specialist by focusing on content creation and authorship, rather than optimization. Responsibilities and Impact: - Write and edit content across formats: web pages, landing pages, social media, campaign assets, and UX copy for digital experiences. - Own our organic social media (LinkedIn and YouTube) channels by developing promotional content, engaging with relevant stakeholders and influencers to elevate our brand awareness. - Serve as the primary author for long-form content in our North America sales solution portfolio (white papers, eBooks, reports). Collaborate with analysts, product experts, and marketing partners to generate and develop compelling content ideas. - Partner with the Digital Content & SEO Specialist to incorporate keyword research and performance insights into content planning (but maintain authorship focus). - Support content migration, ensuring copy aligns with brand voice and user experience needs. - Adapt long-form content into shorter promotional pieces (blog posts, social snippets, email copy) to maximize reach. - Maintain consistency in tone, style, and messaging across all deliverables. What We're Looking For: Basic Required Qualifications: - Strong writing portfolio demonstrating ability to create both digital copy and long-form assets. - 3+ years of experience in content marketing, copywriting, or editorial roles. - Experience with social media management. - Familiarity with SEO and digital publishing best practices (not a core function, but ability to collaborate with SEO lead). - Ability to collaborate with subject matter experts and translate technical insights into customer-facing content. - Highly organized, detail-oriented, and able to manage multiple projects at once. - Ability to learn new technologies quickly and stay on top of emerging content and social media trends. - Experience in B2B, technology, or research-driven industries as a plus. - Experience in B2B technology, automotive, or mobility industry sectors with understanding complex product ecosystems - Familiarity with SEO best practices and content optimization techniques for search engine visibility - Knowledge of marketing automation workflows and nurturing strategies through content touchpoints - Experience collaborating with technical teams and understanding of web analytics, conversion tracking, and digital marketing technology stacks About S&P Global Mobility: S&P Global has recently announced the intent to separate our Mobility Segment into a standalone public company. Compensation/Benefits Information (US Applicants Only): S&P Global states that the anticipated base salary range for this position is $64,387-$97,382. 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 eligible to receive additional S&P Global benefits. Right to Work Requirements: This role is limited to persons with indefinite right to work in the United States. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! It is the policy of Mobility to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, Mobility will provide reasonable accommodations for qualified individuals with disabilities.

• Perform hands-on Application Security assessments including Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), Software Composition Analysis (SCA), and manual code reviews. • Identify, analyze, and remediate vulnerabilities in web, mobile, and API applications (OWASP Top 10, API Security, etc.). • Lead and support Software Supply Chain Security initiatives: Dependency vulnerability management, SBOM (Software Bill of Materials) generation and analysis. • Conduct threat modeling for applications and integration points. • Review and secure build pipelines, container images, and third-party libraries. • Work closely with development, DevOps, and infrastructure teams to embed security into the SDLC. • Monitor and triage security findings from various AppSec tools. • Support Cloud Security posture reviews (basic knowledge required) – IAM, network security, and cloud misconfigurations. • Prepare clear security reports, risk assessments, and remediation guidance for stakeholders. • Stay updated with emerging threats in application security and software supply chain attacks (e.g., SolarWinds, Log4j, dependency confusion).

• Develop and execute a comprehensive operational analytics strategy and roadmap aligned with Enterprise PMO Ops pillar objectives and overall S&P Global Ratings strategic priorities. • Collaborate with IT and Data Governance teams to ensure the availability, quality, and integrity of data used for APMO analytics. • Design, develop, and maintain robust performance dashboards and reports to monitor key APMO metrics. • Identify opportunities for process improvement based on data analysis. • Explore and implement predictive analytics techniques to forecast initiative outcomes, identify potential risks, and optimize resource allocation. • Build strong relationships with key stakeholders across Ratings and Enterprise to understand their analytics needs and deliver tailored solutions. • Evaluate and recommend new analytics tools and technologies to enhance APMO capabilities.

• Design workflow automation solutions using enterprise automation platforms or similar tools to streamline operations for internal and external clients • Create AI-powered agents to automate tasks and improve user efficiency • Build and maintain retrieval-augmented generation (RAG) applications and LLM-powered solutions using vector databases and orchestration frameworks to enhance data retrieval and generation capabilities • Work with business teams to analyze data, build pipelines, and identify automation opportunities • Drive business decisions based on insights obtained from data

• Complete SDLC: architecture, design, development and support of tech solutions • Active participation in all scrum ceremonies, follow SAFe best practices effectively. • Play a key role in the development team to build high-quality, high-performance, scalable code. • Produce technical design documents and conduct technical walkthroughs. • Document and demonstrate solutions using technical design docs, diagrams and stubbed code. • Work collaboratively with business partners to understand and clarify requirements. • Collaborate effectively with technical and non-technical stakeholders. • Design and develop industry-leading applications. • Respond to and resolve production issues.

• Design, configure, and customize ServiceNow applications using Business Rules, Script Includes, Client Scripts, UI Policies, and Catalog UI Scripts. • Utilize Flow Designer and Workflow Editor for automation and process orchestration. • Develop Scoped Applications and reusable components that follow ServiceNow best practices. • Maintain system performance, query optimization, and efficient script execution. • Build role-based access (ACLs) for HR data privacy and security. • Implement and enhance HR Case Management, HR Knowledge, HR Lifecycle Events, and Employee Document Management. • Configure HR Profiles, HR Templates, and Case Forms to match HR processes (onboarding, offboarding, payroll, leave, benefits, etc.). • Build HR Service Catalog items with guided forms, approval flows, and fulfillment tasks. • Implement document generation and e-signature integrations (DocuSign, Adobe Sign). • Configure and extend Agent Chat for HR service delivery, enabling seamless live HR interactions. • Design and implement Virtual Agent topics for common HR inquiries, integrated with HR cases and knowledge articles. • Configure Advanced Work Assignment (AWA) for routing chat requests to the right HR agents based on skills, availability, and capacity. • Personalize Employee Center / Service Portal to support chat, case deflection, and HR self-service. • Develop custom portal widgets using AngularJS, HTML, CSS, and ServiceNow APIs to enhance user experience. • Leverage Flow Designer to automate HR case lifecycle events, document generation, and notifications. • Create subflows, reusable actions, and spokes for HR processes and integrations. • Transition legacy Workflows into Flow Designer where applicable. • Integrate Flow Designer with IntegrationHub for orchestrating end-to-end HR processes. • Develop and maintain real-time and batch integrations between ServiceNow HRSD and external HR systems (Workday, Payroll, Identity Systems, etc.). • Build IntegrationHub Spokes and actions for seamless HR process automation. • Implement REST/SOAP APIs, JDBC, and File-based integrations as per business needs. • Ensure secure and compliant handling of PII data exchange during integrations.

Role Description The Senior Analyst, Data Integration & Workflows plays a critical role within the Data AI & Enablement organization, serving as a senior technical leader responsible for designing, implementing, and operationalizing production-grade data pipelines and workflow automation that power SPDJI's index and analytical solutions. This role combines hands-on technical expertise with leadership capabilities to drive delivery excellence, mentor technical talent, and ensure all data integration solutions meet enterprise standards for quality, reliability, and maintainability. Responsibilities and Impact - Technical Leadership & Solution Delivery - Lead complex data integration initiatives from design through production deployment, ensuring solutions are scalable, observable, and aligned with enterprise architecture standards. - Design and implement production-grade data pipelines (batch and streaming) that transform raw inputs into trusted curated outputs, incorporating robust error handling, validation, and reconciliation controls. - Establish and evangelize engineering best practices for ETL/ELT patterns, workflow orchestration, data quality controls, and operational observability across the team and value streams. - Drive technical decision-making for pipeline architecture, technology selection, and design patterns, balancing business requirements with technical feasibility and long-term maintainability. - Partner with PPD on technical planning and feasibility, providing realistic estimates, identifying technical dependencies, and shaping scope to ensure achievable delivery commitments. - Enablement & Co-Development - Lead hands-on enablement with value stream SMEs through pair programming, structured guidance, and co-development sessions—adapting approach based on SME technical capability. - Assess SME technical readiness and recommend appropriate engagement models (SME-led with review, co-development, or led build with validation). - Build reusable automation components and templates (frameworks for ingestion, validation, transformation, publishing, backfills) that accelerate consistent delivery across domains. - Develop SME technical capabilities through targeted coaching, code reviews, and knowledge transfer, fostering a culture of engineering excellence and continuous learning. - Create and maintain technical documentation, including reference architectures, design patterns, coding standards, and implementation guides. - Quality Assurance & Production Readiness - Conduct comprehensive code reviews for SME-built and team-developed pipelines, ensuring adherence to standards for maintainability, testing, logging, data validation, and documentation. - Implement data reliability controls including validation rules, reconciliation checks, anomaly detection, and completeness/timeliness monitoring that protect downstream index processes. - Engineer observability and monitoring solutions by implementing logging standards, metrics, alerts, and runbooks that enable effective production support. - Prepare IT-ready handover artifacts including technical documentation, test evidence, operational procedures, and clear support boundaries. - Partner with IT during QA and deployment, resolving issues quickly and ensuring solutions meet enterprise standards for security, supportability, and operational excellence. - Operational Excellence & Continuous Improvement - Provide L3 support for production business-logic issues, collaborating with value stream SMEs to drive root-cause analysis and implement permanent fixes for recurring failures. - Optimize pipeline performance and cost through appropriate partitioning strategies, caching, incremental processing patterns, and compute resource tuning. - Implement workflow orchestration patterns (scheduling, dependency management, retries, idempotency, parameterization) ensuring pipelines are resilient to upstream variability. - Capture and share lessons learned, updating engineering playbooks, patterns, and standards based on production outcomes and emerging best practices. - Monitor operational metrics related to pipeline reliability, data quality, performance, and cost efficiency; drive continuous improvement initiatives. - Collaboration & Stakeholder Management - Collaborate with Data Integration Lead to shape team strategy, prioritize initiatives, and align technical approaches with organizational goals. - Partner effectively with AI Solutions and Data Governance teams on cross-cutting concerns including data quality standards, AI pipeline requirements, and compliance. - Engage with Data Value Streams to understand business requirements, validate technical solutions, and ensure alignment with domain expertise. - Work with Data Services & Strategy teams (Vendor Governance, Catalog) to establish scalable integration patterns and ensure proper metadata and lineage tracking. - Build strong relationships with IT and PPD teams to ensure infrastructure readiness, smooth deployments, and operational excellence. - Shared Accountabilities - With Data Integration Lead: Execute on team strategy; provide technical leadership on complex initiatives; mentor junior team members; contribute to standards and capability development. - With PPD: Collaborate on technical feasibility assessments and planning; provide realistic estimates; align integration efforts with platform capabilities and roadmap. - With IT: Ensure infrastructure readiness; coordinate handover processes; support production gateway requirements; partner on operational excellence. - With Data Value Streams: Co-develop solutions with SMEs; validate business logic alignment; assess and develop SME technical capabilities. - With Data Services & Strategy: Establish scalable integration patterns; ensure proper metadata and lineage tracking; align with vendor governance requirements. - With AI Solutions & Data Governance: Coordinate on data quality standards, AI data pipeline requirements, and governance compliance. - Ownership - Complex Technical Initiatives: Own the end-to-end delivery of high-complexity data integration and workflow automation projects. - Engineering Standards Implementation: Responsible for implementing and enforcing technical standards, patterns, and best practices within assigned domain or value streams. - SME Technical Development: Own the hands-on enablement and capability development of assigned value stream SMEs in data engineering practices. - Production Solution Quality: Accountable for ensuring all solutions meet production readiness criteria before IT handover. - Parameters for Success - Deliver Production-Ready Solutions: Consistently deliver high-quality, production-ready data pipelines that meet business requirements and enterprise standards. - Build SME Capability: Demonstrably improve technical capabilities of value stream SMEs through effective enablement and mentorship. - Drive Reusability: Create and promote adoption of reusable components and standardized patterns that accelerate delivery. - Ensure Operational Excellence: Implement robust observability, monitoring, and support frameworks that minimize production incidents and enable rapid issue resolution. - Foster Technical Excellence: Contribute to a culture of craftsmanship, continuous improvement, and engineering best practices. - Key Performance Indicators (KPIs) - Solution Delivery Quality: Percentage of delivered pipelines that pass IT QA on first submission; production incident rate for delivered solutions. - SME Capability Development: Measurable improvement in technical skills of mentored SMEs through assessments, code review quality progression, and feedback. - Operational Reliability: Pipeline uptime and reliability metrics; mean time to resolution for production issues; data quality incident rates. Qualifications - Bachelor's degree in Computer Science, Engineering, Information Systems, or related field; Master's degree preferred. - 8+ years of experience in data engineering, data integration, or related technical roles with progressive responsibility. - 3+ years of experience in technical leadership roles, including mentoring engineers and leading complex technical initiatives. - Proven track record of designing and implementing production data pipelines in complex enterprise environments. - Experience in financial services, index management, or similar data-intensive industries preferred. Requirements - Proficiency in ETL/ELT design patterns, data pipeline architecture, and workflow orchestration frameworks. - Advanced programming skills in languages commonly used in data engineering (Python, SQL, Scala, or similar). - Solid understanding of data quality frameworks, data validation techniques, reconciliation patterns, and anomaly detection. - Experience implementing observability, monitoring, and alerting systems for production data pipelines. - Familiarity with data governance principles, metadata management, and compliance frameworks. Leadership & Soft Skills - Strong technical leadership with demonstrated ability to lead complex initiatives and influence technical direction. - Excellent mentorship and coaching abilities, with track record of developing technical talent and improving team capabilities. - Outstanding collaboration skills with ability to partner effectively across technical and business teams in a matrixed organization. - Clear communication abilities, able to articulate complex technical concepts to varied audiences and translate business requirements into technical solutions. - Problem-solving mindset with focus on root-cause analysis, sustainable solutions, and continuous improvement. - Adaptability and pragmatism in selecting appropriate engagement models based on SME capability and project requirements. - Strong stakeholder management skills with ability to manage expectations and deliver on commitments. Preferred Qualifications - Experience with index calculation processes, financial data workflows, or SPDJI products and methodologies. - Certification in Python or SQL Development (e.g., Python Institute, Microsoft SQL certifications). - Experience with Agile/Scrum methodologies and product-oriented delivery models. - Knowledge of data lineage, metadata management, and data cataloging tools (e.g., Collibra, Alation, DataHub). - Experience with AI/ML data pipeline requirements and integration patterns. Benefits - Health & Wellness: Health care coverage designed for the mind and body. - Flexible Downtime: Generous time off helps keep you energized for your time on. - Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. - Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. - Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in-class benefits for families. - Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

• Process and analyze financial documents received from General/Limited Partners, including capital calls, distributions, financial statements, and schedules of investments. • Access GP portals and repositories to download, categorize, and tag fund-related documents with accurate metadata. • Extract, standardize, and validate data from Private Equity documents such as Partners’ Capital Account statements, cash flow statements, and investment schedules. • Identify appropriate accounting breakouts and classify data items related to fund-level investments and portfolio companies. • Perform data quality checks, resolve exceptions raised through manual QC reviews and automated validation logs, and ensure adherence to defined data standards. • Conduct routine reporting and basic trend analysis to support internal analytics and operational insights. • Support data cleansing initiatives to improve accuracy and consistency across datasets. • Assist with process improvement, Lean initiatives, and automation efforts, including basic SQL-driven data tasks. • Maintain clear documentation of data collection and validation processes for auditability and future reference. • Collaborate with team members to deliver individual and team targets with a strong focus on quality, accuracy, and timeliness. • Participate in ad-hoc projects aligned to business expansion, data enhancement, or automation initiatives.

• Working with stakeholders and senior team members to understand and clarify requirements for a data platform and associated applications. • Designing and implementing full stack features for applications, incorporating technical elements from database through to user interface under established patterns and guidance. • Building and maintaining APIs and service components to support platform workflows, following team standards for versioning, security, and performance. • Contributing to microservices and event-driven components by implementing defined stories, integrations, and message handlers with guidance as needed. • Participating in reporting, data management, and operational tooling efforts by delivering incremental enhancements and fixes. • Supporting system reliability, performance, and security by identifying defects or workflow gaps, writing fixes, and contributing to reviews and test coverage. • Collaborating with distributed team members through code reviews, pairing, and shared ownership of delivery outcomes. • Contributing to CI/CD practices by maintaining build quality, improving test automation, and supporting deployments with guidance. • Participating in production support as needed (triage, troubleshooting, and defect resolution), escalating appropriately.

• Lead complex data integration initiatives from design through production deployment, ensuring solutions are scalable, observable, and aligned with enterprise architecture standards • Design and implement production-grade data pipelines (batch and streaming) that transform raw inputs into trusted curated outputs, incorporating robust error handling, validation, and reconciliation controls • Establish and evangelize engineering best practices for ETL/ELT patterns, workflow orchestration, data quality controls, and operational observability across the team and value streams • Drive technical decision-making for pipeline architecture, technology selection, and design patterns, balancing business requirements with technical feasibility and long-term maintainability • Partner with PPD on technical planning and feasibility, providing realistic estimates, identifying technical dependencies, and shaping scope to ensure achievable delivery commitments • Conduct comprehensive code reviews for SME-built and team-developed pipelines, ensuring adherence to standards for maintainability, testing, logging, data validation, and documentation • Prepare IT-ready handover artifacts including technical documentation, test evidence, operational procedures, and clear support boundaries • Optimize pipeline performance and cost through appropriate partitioning strategies, caching, incremental processing patterns, and compute resource tuning.