• Design, build, and maintain enterprise data architectures supporting Supply Chain execution and performance measurement • Develop data models, pipelines, and integration frameworks • Lead data migrations, conversions, and performance optimization efforts • Oversea testing, deployment, maintenance, and continuous improvement of data systems • Ensure adherence to data quality, security, and compliance standards

Title: Chapter Lead, Data Science (Operations) Location: Australia Full time Job requisition id REQ248859 Job Description: Permanent Full Time Opportunity Drive the future of AI innovation at scale You are a visionary leader with a growth mindset, combining deep technical fluency with the ability to inspire and scale impact across the enterprise. Were one of the largest and most advanced Data Science practices in the country Together we can build state-of-the-art Data Science models that power seamless experiences for millions of customers See yourself in our team At the heart of the Chief Operations Office (COO), we're reimagining how we serve customers in operations through the power of transformative AI solutions. As a Chapter Lead reporting to the Chapter Area Lead of Data Science in COO, you'll balance hands-on technical contribution with people leadership-guiding and growing a team of data scientists while working in cross-functional squads with engineers and other experts to design and deliver innovative, responsible AI solutions. You'll stay at the forefront of emerging technologies, fostering a culture of curiosity, inclusion, and continuous learning, and translating complex ideas into high-impact outcomes for customers and colleagues. If you're passionate about shaping the future of AI while helping others thrive, we'd love you to lead with us. Key Responsibilities Lead AI Innovation Drive the design, construction and deployment of a range of AI projects Accelerate adoption of advanced AI capabilities Expand Data & AI Impact Across the Bank Identify high‑value AI use cases and champion the integration of Data Science methods across processes Ensure models follow best-practice engineering, governance, and deployment standards Drive Continuous Improvement & Business Value through AI Partner closely with operations teams to understand challenges and apply transformative AI capabilities Drive redevelopment, optimisation and monitoring of AI models to support strategic business outcomes We're interested in hearing from people with the following skills: Technical & People Leadership Demonstrated capability in driving outcomes that are reusable and can be leveraged across the group Demonstrated intellectual curiosity with a passion for experimenting and exploring emerging technologies Demonstrated ability to lead and mentor teams while remaining hands-on, fostering a supportive and inclusive team culture that values learning, thoughtful decision-making, and sustainable delivery of real-world impact. Technical Expertise Data: Experience designing and delivering AI solutions using a range of structured and unstructured data, with particular strength in natural language data. Machine Learning: Strong grounding in classical machine learning and deep learning, with the ability to select appropriate techniques-from simpler models to more complex approaches-based on problem context, constraints, and impact. Generative AI: Hands-on experience designing, building, and deploying Generative AI solutions, including RAG and agentic systems, with a pragmatic understanding of their limitations, risks, and costs. Statistical Expertise: Experience defining fit-for-purpose evaluation metrics, guiding experimentation, and applying sound statistical judgement to technical decision-making across the AI lifecycle. Production AI & MLOps: Proven ability to take models from prototype to production, including version control, CI/CD practices, containerisation, deployment, monitoring, and ongoing iteration. Data Engineering & Architecture: Working knowledge of data pipelines and integration patterns, and experience collaborating on scalable, reliable data and AI architectures. Cloud Platforms: Experience designing or deploying AI solutions on cloud platforms such as AWS or Azure, with awareness of scalability, cost, and operational considerations. Technical Leadership & Delivery: Ability to lead and mentor teams while remaining hands-on, balancing curiosity and continuous learning with a strong focus on delivery, value creation, and real-world impact. Working with us At CommBank, we advocate and facilitate a culture of inclusion and respect, celebrating all cultures, abilities, genders, expressions of gender and sexual orientation Read more about our commitment to inclusion and diversity. Our people bring their diverse backgrounds and unique perspectives to build a respectful, inclusive, and flexible workplace. One where we're driven by our values, and supported to share ideas, initiatives, and energy. One where making a positive impact for customers, communities and each other is part of our every day. We're committed to being an accessible employer and want to make finding your dream job as easy as possible. If you experience any accessibility issues or if you require additional support, please contact HR Direct. We support our people with the flexibility to balance where work is done with a hybrid approach of at least half your time each month connecting in office. We also have many other flexible working options available including changing start and finish times, part-time arrangements and job share to name a few. Talk to us about how these arrangements might work for you. Here, you'll thrive. You'll be supported when faced with challenges and empowered to tackle new opportunities. We're hiring talent from across all of Australia and have opened technology hubs in Melbourne and Perth. We really love working here, and we think you will too. If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We're keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users.

Title: Lead, Data Governance (Master Data Management) Location: Hoboken United States Job Description: Workplace Type: Remote Job: Data Engineering Schedule: FULL_TIME Req ID: 24896 OCTO Global Data | Pearson Role Overview Pearson's data organization is in the middle of a genuine transformation and master data is the foundation it's being built on. We're not here to maintain the status quo. We're rethinking how a global education company defines, trusts, and activates its most critical data assets. We're looking for a Lead, Data Governance (Master Data Management) to lead this charge: setting the strategy, defining the architecture, and driving the execution of Pearson's enterprise master data capabilities. You'll start with the Customer domain, working through the legacy complexity while simultaneously building the blueprints for how we govern Product, Supplier, and other critical domains in a fundamentally different way. This is a senior, player-coach role for someone who can hold two things at once: the pragmatism to tackle what's broken today, and the ambition to reinvent how an enterprise thinks about data. You will be shaping Pearson's philosophy around trusted, reusable, governed data and building the systems, products, processes, and culture to make that real. You'll operate as a thought leader to the business, not just a technical function. That means influencing how Pearson's most senior stakeholders understand and value their data, advocating for data as a strategic product, and helping the organization move from treating data as a byproduct of operations to treating it as a first-class asset. This role sits within Global Data, a team of builders in the middle of a meaningful modernization. You'll work at the intersection of data engineering, data products, analytics, and business units across a global organization, with the ability to drive real change. Key Responsibilities MDM Strategy & Architecture - Drive MDM vision and roadmap: Define and execute the enterprise master data strategy across the Customer domain and beyond (product, supplier, employee, finance) with a phased roadmap for domain expansion. Challenge the status quo and question inherited ways of working, bring fresh thinking to how best practices are defined, and push the organization toward modern, scalable approaches that reflect where data management should be going. - Establish best practices: Design and implement MDM architecture standards that serve Pearson's global needs while enabling business units to achieve their goals. - Data governance: Build and operate a data governance framework including stewardship models, data ownership policies, and dispute resolution processes across BUs. - Architecture and Design: Define system-of-record vs. system-of-use vs. system-of-truth across Salesforce, Oracle, E-commerce, and other integrated platforms. Drive data model re-design reducing MDM data bloat and ensuring streamlined field use across all BUs and functions. - Metadata & lineage: Oversee metadata management and data lineage practices to ensure traceability and auditability across the data estate. - Automation: Identify automation opportunities as it relates to master data CRUD or Data quality. Customer360 & Self-Service Analytics - Lead Customer360 data product: Lead the design and build of holistic view of the Pearson customer, a foundational data product that powers self-service analytics across the business. - Innovative data access: Create and champion new approaches to accessing and consuming master data, enabling business users to answer their own questions without reliance on data teams. - Single source of truth: Drive the design and adoption of golden record and deduplication processes, match and merge logic that produces a trusted, unified view of each customer across all Pearson systems. 1. Data Quality & Trusted Data - Data quality ownership: Define and enforce data quality standards across master data domains, profiling, monitoring, cleansing, and continuous improvement. - Golden record & deduplication: Lead the design of match and merge processes to identify, resolve, and prevent duplicate records across source systems. - Data stewardship program: Stand up a data stewardship program that embeds accountability for data quality within business units, not just central IT. Production Support & Legacy Systems - Legacy system stabilization: Partner with engineering and operations teams to drive production support for legacy MDM systems while the organization transitions to modern platforms. - System integration: Ensure master data flows correctly across Oracle, Salesforce, and other enterprise systems, managing integration patterns, data synchronization, and API-based consumption. - ETL/ELT pipelines: Oversee the design and maintenance of data ingestion pipelines that feed master data from source systems into the MDM platform. - Master Data Migrations: Support master data migration programs ensuring data quality, standard processes, and approvals are in place before creating or updating data. 1. - Cross-Functional Partnership & Change Management - Stakeholder influence: Act as the primary MDM partner to business units, translating complex data capabilities into business value and influencing across a matrixed organization. - Change management: Drive the cultural and operational change required for MDM transformation, MDM programs succeed or fail based on adoption, not just technology. - Business & technical fluency: Serve as the bridge between technical data teams and business stakeholders, with a deep understanding of both Pearson's data landscape and the commercial needs of its business units. - Program Leadership: Serve as the central MDM lead across all major enterprise programs and ensure alignment of requirements and dependencies across the programs. - Performance Management and Continuous Improvement: Define and track KPIs tied to business outcomes and MDM value realization Qualifications Required - 10–15 years of experience in data management, with significant depth in Master Data Management - Hands-on experience with MDM platforms such as Informatica - Deep knowledge of Oracle and Salesforce as source systems and MDM consumers (SFDC – Data360 and Agentforce) - Proven experience designing match and merge logic, deduplication, and golden record processes - Large Scale Customer Master / Customer 360 transformations - Deep understanding of data governance frameworks, data stewardship, and data ownership models - Experience with ETL/ELT pipelines, API integration patterns, and cloud data platforms - Track record of driving data quality programs at scale in complex enterprise environments - Ability to lead cross-functional initiatives and influence senior stakeholders without direct authority - Experience managing legacy system environments while driving modernization - Strong communication skills - able to translate technical concepts for business audiences and vice versa Nice to Have - Experience with data product thinking and self-service analytics enablement - Familiarity with Customer360 or similar enterprise customer data initiatives - Experience with GCP (Looker) - Experience with metadata management tools and data lineage platforms - Knowledge of real-time and streaming data architectures Benefits at a Glance We know you’ll do great work, so we give a lot back with some of the best benefits in the business. We know one size doesn’t fit all, so our workplace programs meet the different needs of our diverse teams, and their families, too. See our Benefits. At Pearson, we’re transforming learning. If you’re a Technology leader who thrives in complexity, leads with purpose, and aspires to shape the future—we want to hear from you. Apply today and imagine the impact you can make. Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. The full-time salary range is between $200,000 - $220,000. This position is eligible to participate in an annual incentive program, and information on benefits offered is here. #LI-EB1 Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing Job: Data Engineering Job Family: TECHNOLOGY

• Evaluate the existing data architecture and propose structural improvements. • Organize and standardize the company's data environment, promoting stronger governance and scalability. • Define architectural standards, best practices, and technical guidelines for the organization. • Review data flows, integrations, pipelines, and data models, identifying optimization opportunities. • Ensure data consistency, quality, security, and governance. • Serve as a technical reference for data architecture–related initiatives. • Support technology teams in defining architectural best practices. • Collaborate with global leadership to define the company's data strategy. • Produce technical and architectural documentation in English. • Participate in strategic meetings with international teams.