• Serve as the primary delivery partner for the Streaming Intelligence product line and DPT, converting roadmap priorities into actionable project plans with clear milestones, owners, and dependencies. • Co-own quarterly and annual planning with the Principal PM—from ideation through go-to-market—ensuring engineering capacity, vendor timelines, and business priorities are aligned. • Track and report on product line KPIs defined by the Principal PM (accuracy benchmarks, processing latency, content coverage, downstream adoption) and surface risks or deviations early. • Partner with the data team on agentic AI enablement—coordinating efforts to surface data models and semantic views to the broader business through AI-powered interfaces, including usage tracking and accuracy assurance. • Manage delivery cadence for platform infrastructure initiatives including data governance rollouts, real-time streaming capabilities, and pipeline migration efforts—tracking phased delivery across multiple months with clear metrics of success. • Lead end-to-end program management for AI pipeline initiatives, including the game film analysis benchmarking program that evaluates vision models (e.g., Gemini Flash, Gemini Pro) against human-tagged ground truth across 28+ annotated fields per play. • Manage the cadence of model evaluation cycles: coordinating game imports, prompt engineering iterations, accuracy scoring, and cost analysis across multiple AI models. • Drive vendor integration workstreams—tracking deliverables, SLAs, and roadmap alignment with external computer vision and AI partners alongside the Principal PM. • Build and maintain project documentation for hybrid human-AI workflows, including escalation paths for ambiguous plays, quality review processes, and fallback handling. • Facilitate cross-team visibility across product, engineering, data, design, and QA to ensure aligned execution mapping back to PlayOn’s unified product objectives: Engaged Communities, Resilient Services, and New Customer Markets. • Own dependency mapping, risk management, and blocker resolution for strategic AI initiatives spanning multiple engineering teams. • Develop and maintain project dashboards, status reports, and executive-level communications that increase transparency of engineering progress to the broader business. • Provide governance and optimization for Atlassian tools (Jira, Confluence) to ensure standardized workflows, consistent estimation practices, and clear traceability from strategy to execution. • Champion operational improvements to planning cycles, stakeholder coordination, cross-org meetings, and feedback loops—creating transparency through standardized tooling and repeatable frameworks. • Actively incorporate AI tools (e.g., Claude, automation platforms) into your own delivery workflows: automating status reports, synthesizing meeting notes, generating risk analyses, and accelerating documentation. • Contribute to PlayOn’s broader AI maturity journey by demonstrating AI-augmented delivery practices that can be adopted across the PMO and engineering organization.

Role Description As a Senior Data Warehouse Architect (Data Vault 2.0), you will play a key role in designing, evolving, and optimising enterprise-scale data platforms for our clients. You will work at the intersection of data architecture, engineering, and business, helping organisations build scalable, reliable, and future-proof data ecosystems. Collaborating with multidisciplinary teams in an international environment, you will drive architectural decisions, establish best practices, and ensure the successful delivery of modern data warehouse solutions. Your Impact - Design, implement, and maintain enterprise data warehouse solutions following Data Vault 2.0 methodology - Develop and optimise Hubs, Links, Satellites, PIT, and Bridge tables - Lead conceptual, logical, and physical data modelling activities across multiple initiatives - Define and promote data architecture standards, modelling guidelines, naming conventions, and documentation practices - Ensure scalability, performance, reliability, and maintainability of data warehouse architectures - Provide technical leadership and architectural guidance to Data Engineers and development teams - Drive the standardisation and automation of ELT processes, metadata management, and deployment practices - Collaborate closely with Business Analysts, Product Owners, Data Governance teams, and other stakeholders to translate business requirements into robust data solutions - Support reporting and analytics teams by delivering optimised and business-ready data structures - Implement and promote best practices related to data governance, lineage, metadata management, and DataOps - Define and enhance monitoring, validation, and observability processes across the data platform - Evaluate emerging technologies and recommend improvements to the overall data architecture landscape What Makes This Role Challenging - You will work with complex enterprise data ecosystems that require scalable and maintainable architectural solutions - The role demands deep expertise in Data Vault 2.0 and the ability to apply modelling standards consistently across multiple initiatives - You will balance long-term architectural vision with immediate business and delivery requirements - The position requires close collaboration with both technical and business stakeholders, translating complex requirements into effective data models - You will drive governance, quality, and standardisation efforts while enabling innovation and scalability - The environment combines modern cloud data platforms, large data volumes, and evolving business needs Qualifications - Minimum 7 years of experience in Data Engineering, Data Architecture, Business Intelligence, or Data Warehouse environments - Proven expertise in Data Vault 2.0 modelling and architecture - Strong experience designing and implementing enterprise-scale Data Warehouse solutions - Advanced SQL skills and strong data modelling expertise - Experience with modern cloud data platforms (Snowflake, Databricks, etc.) - Experience with ETL/ELT tools and orchestration frameworks (DBT, Airflow, etc.) - Strong understanding of Data Governance, Metadata Management, Data Lineage, Master Data Management (MDM), and DataOps practices - Experience providing technical leadership and architectural guidance to engineering teams - Excellent communication and stakeholder management skills - Strong analytical and problem-solving abilities - Fluency in English - Must be a Portuguese or European citizen, or hold a valid work permit for Portugal Nice-to-haves - Data Vault 2.0 certification - Experience with event-driven or real-time data architectures - Knowledge of Python and/or Scala for automation and data engineering activities - Experience mentoring engineers, leading technical initiatives, or guiding architecture communities - Exposure to cloud-native data platform architectures - Exposure to international or multicultural projects - Experience working in consulting or client-facing environments Benefits - Competitive salary aligned with your experience and the data market - Meal allowance: €10.20/day - Flexible benefits plan - Private medical insurance - 22 days of annual leave, increasing every 3 years (up to 25 days) - Continuous learning via KLX – Keyrus Learning Experience - A collaborative, international, and human-centred work environment Equal Opportunity Statement We are committed to building an inclusive workplace and encourage applications from all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, age, disability, or any other protected characteristic.

• Designing and maintaining scalable database architectures for analytical workloads, ensuring optimal performance through indexing, partitioning, caching, and query tuning. • Developing, automating, and maintaining data ingestion, transformation, validation, and loading pipelines to support high-quality data flows. • Building reusable data connection modules and backend infrastructure components to streamline data operations and support future scalability. • Supporting data preprocessing, normalization, and rigorous data quality validation processes. • Contributing to cloud migration planning, governance, and evaluation of cloud solutions for security, compliance, interoperability, and performance. • Producing comprehensive data models, architecture diagrams, flowcharts, and technical documentation for internal and external stakeholders. • Utilizing PowerShell scripting and automation to enhance data engineering workflows and system integration. • Collaborating with technical, security, and stakeholder teams throughout the project lifecycle to deliver high-impact data solutions.

• Design the vision and blueprint of the organization's data framework to support public health informatics objectives. • Design and manage data systems, establishing policies for how data is stored, accessed, and governed. • Coordinate various data sources within the organization to ensure consistency and integrity across the data environment. • Integrate new data technologies into existing IT infrastructures. • Perform data modeling and design activities to support reporting, analytics, and operational needs. • Develop and maintain ETL pipelines to support data movement and transformation. • Write and optimize SQL queries in support of data operations and system requirements. • Administer database environments in coordination with application and infrastructure teams. • Submit weekly status reports detailing completed and ongoing project activities, including risks as applicable. • Maintain accurate records of work performed and hours expended in accordance with OTS Task Order requirements.