The Indiana Health Information Exchange (IHIE) is one of the nation’s largest health information exchange organizations. IHIE has been around for over a decade, with its roots dating back 30 years. As a not-for-profit HIE, we enable hospitals, physicians, laboratories, payers, and other health service providers to avoid redundancy and deliver faster, more efficient, higher quality healthcare to patients in Indiana. Today, by making information available to approximately 50,000 healthcare providers in Indiana and neighboring states, we deliver services that make a real difference in health and healthcare.****We are seeking an experienced Oracle-focused Analytics Data Engineer II to support IHIE’s data roadmap and build high-quality data assets that power clinical insights, products, and customer-facing analytics. This role requires highly skilled engineers who understand Oracle performance tuning, healthcare data standards, and the practical realities of designing pipelines at scale.****If you are talented, driven, collaborative, and enjoy solving complex data problems that make a difference, IHIE is a great place to grow.******Summary: **The Oracle Data Engineer II serve as technical contributor responsible for building and optimizing IHIE’s analytic datasets, data quality pipelines, and customer-facing data deliverables. This individual is a subject matter expert in Oracle SQL, PL/SQL, data modeling, and healthcare data standards. This individual collaborates closely with Solution Engineering, Product, and business stakeholders to ensure data assets are accurate, performant, and aligned with organizational priorities.************Job Function Risk Level 3: **Privileged user access with intentional access to PHI and sensitive data

Overview Build the Future At McGraw Hill, we are dedicated to delivering digital learning experiences that transform education for learners and educators. Our focus is on creating seamless, impactful products that truly benefit our users while supporting growth and collaboration across teams. We foster a culture that values innovation, teamwork, and a balance between career growth and personal well-being. How can you make an impact? The Cybersecurity Engineer – AI & DLP is responsible for designing and implementing data protection and governance controls across enterprise AI platforms, such as generative AI and AI-assisted development tools. This position centers on preventing data leaks, overseeing AI interactions with sensitive information, and applying security policies using DLP technologies, logging, and automated controls. The engineer will assess risks associated with AI platforms, set up inspection and monitoring systems, and create governance frameworks that ensure AI tool usage complies with organizational security, privacy, and compliance standards. This is a remote position open to applicants authorized to work for any employer within the United States. What You'll Do: - Define and implement AI security controls, such as prompt filtering, response inspection, redaction, and usage monitoring, to ensure enterprise AI tools operate within approved data protection and compliance boundaries. - Evaluate inputs and outputs of enterprise AI tools (e.g., ChatGPT, Claude, and internal LLM platforms) to identify risks related to sensitive data exposure, prompt injection, and intellectual property leakage. - Design and implement technical guardrails and monitoring controls—including prompt inspection, output filtering, and DLP policies—to ensure AI usage aligns with enterprise security and data governance standards. - Design, implement, and operate Data Loss Prevention (DLP) controls to prevent the exposure of sensitive data across enterprise AI platforms and generative AI tools. - Partner with engineering, AI/data science, and Digital Workspace teams to integrate security controls into AI platforms, including prompt monitoring, data classification, and access controls. - Evaluate emerging AI tools, models, and AI-assisted development platforms to identify cybersecurity risks and recommend appropriate security requirements and mitigations. - Implement logging, monitoring, and alerting capabilities to provide visibility into how enterprise data is accessed, processed, and shared through AI systems. - Develop and enforce policies and technical controls that prevent the use of sensitive data (e.g., PII, credentials, proprietary content) within AI prompts, training datasets, or integrations. - Design and implement a Data Loss Prevention (DLP) strategy throughout all MH infrastructure systems (MS Purview, Zscaler, cloud environments). Operationalize the alert and triage standard operating procedures to protect sensitive emails, uploads, and other avenues of data loss. - Support the design of secure architecture for enterprise AI platforms, including controls for data handling, model access, API usage, and third-party integrations. - Contribute to security awareness and guidance for developers and employees on safe and responsible use of generative AI tools. Who You Are: - 15+ years of applicable experience. - Bachelor's degree in computer science, Engineering, or related field. - Strong communication skills and comfortability working directly with business stakeholders, vendors, and leadership. - Ability to present risks and recommendations to leadership. - Ability to translate complex identity concepts into business value. - Understanding the Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and API integrations. - Strong knowledge of DLP technical controls, concepts, and end user computing behaviors. - Experience with administration of the Microsoft tool suite, particularly M365 Copilot, GitHub Copilot, Microsoft Purview. Preferred: - In-depth knowledge of agentic AI usage and guardrails from an end user and development perspective. - Knowledge of infrastructure and engineering of client/server compute systems. Why work for us? The work you do at McGraw Hill will be work that matters. We are collectively building experiences that will help shape the future of education. Play your part and experience a sense of fulfilment that will inspire you to even greater heights. The pay range for this position is between $136,000 - $190,000 annually. However, base pay offered may vary depending on job-related knowledge, skills, experience, and location. An annual bonus plan may be provided as part of the compensation package, in addition to a full range of medical and/or other benefits, depending on the position offered. Click here to learn more about our benefit offerings. McGraw Hill recruiters always use a “@mheducation.com” email address and/or from our Applicant Tracking System, iCIMS. Any variation of this email domain should be considered suspicious. Additionally, McGraw Hill recruiters and authorized representatives will never request sensitive information in email. 50575

• Build and operate the data foundation that enables analytics and AI across the organization. • Design, develop, and maintain scalable data pipelines. • Ensure that data from various source systems is reliably integrated and accessible. • Collaborate with Data Architects, Data Scientists, and business stakeholders. • Transform raw data into high-quality, usable data products that support business decision-making. • Monitor and troubleshoot data pipelines and workflows. • Contribute to the development of a modern, cloud-based data platform. • Apply software engineering best practices in data development.

At Heinsohn, we partner with clients across North America and LATAM, building innovative solutions in an agile, diverse, and multicultural environment. We are passionate about technology, continuous learning, and collaboration - and we want you to be part of this growth. We are seeking a conscientious, detail-oriented, and analytical professional to join our team. The role is primarily focused on data labeling and validating labels with other team members. The ideal candidate will have a passion for historical data and genealogy. You will be responsible for identifying patterns and connections, and providing insights that help individuals understand their family history. ✨ Responsibilities - Data Collection and Cleaning: Collect, clean, and process historical family records from various sources, ensuring data quality and accuracy via our in-house data extraction tool. - Pattern Recognition: Identify patterns, relationships, and anomalies in family records across multiple languages. - Historical Research: Collaborate with peers to validate data findings and enhance the understanding of family histories. - Collaboration: Work with cross-functional teams to integrate data findings. - Documentation and Data Validation. ✅ Requirements - Education: Bachelor’s degree and some experience in the data science field. - Experience: Entry to Mid-level professional looking to move into Data Labeling. - Analytical Skills: Excellent problem-solving skills and the ability to think critically and analytically. - Communication: Strong verbal and written communication skills, with the ability to explain complex concepts to non-technical audiences. - Perseverance and attention to detail when working with difficult-to-read documents. - Ability to recognize patterns in historical documents. - Interest in learning to read multiple languages. - English language proficiency: minimum B2 level. 🌟 Benefits - 100% remote work from any LATAM country - Opportunity to work on international projects with multicultural teams - Culture that encourages professional development and continuous learning - Spaces for innovation, well-being, and career growth Ready to take your talent to the next level? At Heinsohn, we value innovation, passion for technology, and teamwork. If this sounds like your next challenge, apply today and let’s make history together! ✨