Want to help us bring happiness to the world? Want to join an ambitious and fast growing global biscuits and confectionery business investing heavily in iconic global brands, infrastructure and people? Then this is the place for you. As proud bakers and chocolatiers and custodians of iconic global brands, we don’t compromise on the quality of ingredients in our products or on the people we hire. We are looking for entrepreneurial spirits who share our passion for bringing happiness to our consumers and who embody our Winning Traits. To succeed at pladis you need to be purpose-led, resilient and positive to succeed here because we expect pace and agility, we insist on collaboration and demand accountability. If that is your thing, then pladis offers global ambition, a clear Vision and roadmap for success, challenge, and unrivalled opportunities to learn and make an impact Click “Apply” to get started. The Head of Data & Analytics Architecture and AI mission has three facets. 1) To own the D&A Architecture ensuring alignment with business objectives and the technology transformation agenda for D&A to provide enabling Digital services such as Data as a Service via APIs and Insights as a Service 2) To own and deliver the technology capability for Data, Analytics and AI (D&A). Working closely with the Squads on a daily basis, the Lead Engineer will help the squads deliver maximum outputs for each sprint ensuring each sprint delivers the longer term technology roadmap and vision. 3) To own the Security, Data Assurance and Quality for both core D&A systems and the wider technology architecture. 1. Data & Analytics (D&A) Infrastructure Management: Develop, maintain, and optimize the D&A architecture on AWS and Azure, including the design, deployment, and maintenance of the cloud based Pladis’ data platform (PDP). Deliver an architecture that's globally scalable, agile, and supportive of digital services through Data and Insights as a service via APIs. 2. Data Technology Capability Enhancement: Design and oversee the implementation of the PDP 2.0 Tech stack. Design and oversee data architecture to harmonise external, internal and Microsoft Graph data to deliver AI use cases Champion engineering standards and ensure new engineers' quick integration and productivity. Lead engineering problem solving and provide technical guidance to squad engineers. Foster a component based delivery approach to enhance reusability across different areas of the business. Collaborate with stakeholders to guarantee timely engineering deliverables and work with partners to accelerate delivery velocity within teams. Implement and review measures to track and enhance data engineering productivity. 3. Data Governance, Security, and Quality: Implement end to end data security measures, including periodic penetration testing, audits, and assurance of PDP. Coordinate with the CISO, DPO, and other teams to ensure data security, GDPR compliance, and overall data assurance. Initiate and oversee a continuous data quality improvement strategy both at PDP and in source systems. 4. AI & Advanced Analytics Strategy and Vision: Set and align the AI architecture vision with the company’s overarching business goals. Stay updated with latest AI and ML trends to keep the company at the technological forefront. Lay down AI architectural standards, best practices, and guidelines for system design. 5. AI Solutions Design and Integration: Design AI solutions that are robust, scalable, and in line with business requirements. Integrate generalized AI models into business processes and ensure they harmonize with existing systems. 6. AI Data Management and Storage: Manage and safeguard data for AI models, emphasizing governance, quality, security, and accessibility. Design storage solutions optimized for real time processing, querying, and scalability. Collaborate with data teams to streamline AI model lifecycle processes. 7. AI Technical Leadership and Engagement: Mentor and guide AI teams, ensuring alignment with business objectives. Engage regularly with business stakeholders to align AI outputs with business needs. Encourage AI literacy within the company through training and engagement. 8. AI Solution Lifecycle Oversight: Ensure smooth deployment, monitoring, and maintenance of AI models in production environments. Uphold ethical standards and ensure compliance with data privacy regulations. Technical Competencies The role is a hands-on technical leadership role with advanced experience in at least most of the following technologies Cloud Platforms: AWS (Amazon Web Services): Knowledge of services like S3, EC2, Lambda, RDS, Redshift, EMR, SageMaker, Glue, and Kinesis. Azure: Proficiency in services like Azure Blob Storage, Azure Data Lake, VMs, Azure Functions, Azure SQL Database, HDInsight, and Azure Machine Learning Studio. Data Storage & Databases: SQL & NoSQL Databases: Experience with databases like PostgreSQL, MySQL, MongoDB, and Cassandra. Big Data Ecosystems: Hadoop, Spark, Hive, and HBase. Data Integration & ETL: Data Pipelining Tools: Apache NiFi, Apache Kafka, and Apache Flink. ETL Tools: AWS Glue, Azure Data Factory, Talend, and Apache Airflow. AI & Machine Learning: Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, and MXNet. AI Services: AWS SageMaker, Azure Machine Learning, Google AI Platform. DevOps & Infrastructure as Code: Containerization: Docker and Kubernetes. Infrastructure Automation: Terraform, Ansible, and AWS CloudFormation. API & Microservices: API Development: RESTful API design and GraphQL. Microservices Tools: Istio, Envoy, and Linkerd. Security & Governance: Identity & Access Management: AWS IAM, Azure Active Directory. Data Governance Tools: AWS Lake Formation, Azure Purview. Data Security Tools: AWS Key Management Service (KMS), Azure Key Vault. Data Analytics & BI: Visualization Tools: Tableau, Power BI, Looker, and Grafana. Analytics Services: AWS Athena, Amazon QuickSight, Azure Stream Analytics. Development & Collaboration Tools: Version Control: Git (and platforms like GitHub, GitLab). CI/CD Tools: Jenkins, Travis CI, AWS CodePipeline, Azure DevOps. Other Key Skills: IaC (Infrastructure as Code): Mastery in automating infrastructure setup. Serverless Architectures: Experience with AWS Lambda, Azure Functions. Edge Computing: Knowledge of AWS Greengrass, Azure IoT Edge. Networking & Content Delivery: Experience with VPCs, CDN solutions like AWS CloudFront, and Azure Content Delivery Network. Competencies 1. Communication & Leadership: Proficient in English (spoken and written) with strong presentation skills. Servant leadership mindset. Knowledge of regional languages is a plus. 2. Experience: Demonstrated success as a data or enterprise architect. 3. Technical Expertise: Solid knowledge of cloud-based Data & Analytics technologies. 4. Industry Experience: Familiarity with Consumer Packaged Goods, Food Retail, or ecommerce environments is preferred. 5. Efficiency: Produces impactful results without unnecessary waste. 6. Agile Expertise: Deep-rooted understanding of value-driven Agile methodologies. 7. Customer-Centric: Prioritizes customer needs and desired outcomes. 8. Problem-Solving: Capable of effective conflict resolution and creative problem-solving. 9. Integrity & Independence: Honesty and the ability to drive initiatives with minimal oversight. 10. Quick Learner: Exhibits a rapid ability to assimilate and understand new information. 11. Creativity: Finds innovative solutions without compromising quality. 12. Data-Oriented: Makes decisions based on data. 13. Detail-Oriented: Pays meticulous attention to details. 14. Open Communication: Is candid and straightforward in discussions pladis is an Equal Opportunity Employer, committed to hiring a diverse workforce. All openings will be filled based on qualifications without regard to race, color, sex, sexual orientation, gender identity, national origin, marital status, veteran status, disability, age, religion or any other classification protected by law. We operate a strict Preferred Supplier List. If you are a recruitment agency and wish to submit candidate to be considered for this vacancy, you must have agreed to, and signed, our terms of business. We will not accept CVs from any other sources other than those currently on our PSL. We will not pay a fee for any candidate that has not been represented by a provider on our PSL.