{"id":701387,"url":"https://alion.io/job/webuild-ai-data-platform-engineer","title":"Data Platform Engineer","company":{"id":685185,"name":"WeBuild-AI","domain":"webuild-ai.com","url":"https://alion.io/company/webuild-ai","size_band":"1-10","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":80,"open_postings":5,"ghost_share":0,"stale_share":0.8,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":69000,"max_usd":158000,"period":"year","method":"role_country_seniority_unknown","sample_n":202},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Neptune","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Docker","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Kubernetes","optional":false},{"name":"Neo4j","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2025-10-03T00:00:00Z","employer_posted_date":"2025-10-03","last_verified_at":"2026-10-30T19:29:49Z","board_verified":true,"closed_at":null,"days_open":392,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":391},"description":"About WeBuild-AI:\nWeBuild-AI are AI natives delivering 10x value for enterprise organisations. We combine highly skilled experts with our AI Launchpad, industry-aligned language models, and agents to transform enterprise organisations into AI-powered and data-driven businesses. We work with enterprise organisations on a global stage, reinventing how they design, build, and operate AI powered software at scale with speed.\nOur Purpose:\nAt WeBuild-AI, we're not just building data architectures-we're building the foundation for AI-powered business transformation that creates lasting impact. Our teams are pioneering new approaches that fundamentally change how enterprises leverage their data assets, unlocking possibilities that were previously unimaginable. We believe that a modular and composable data architecture is the cornerstone of true AI transformation, and we're looking for visionaries who share our passion for pushing boundaries.\nRole Overview:\nAs a Platform Engineer at WeBuild-AI, you will design and implement cutting-edge data solutions that form the foundation of our customers AI-driven transformations. You'll work with our Pathway platform to enable rapid strategy definition, technology capability validation, and new venture launches for our global enterprise clients. This role offers the unique opportunity to shape how entire industries approach data and AI integration.\nKey Responsibilities:\n Work with clients to understand their data landscape and transformation needs.\n Establish data strategy roadmaps and build scalable data platforms.\nDesign and implement scalable data architectures to support AI-driven solutions.\n Develop data solutions across a raft of AWS and Azure data services.\nDesign and implement data mesh and data fabric solutions to optimise datadiscover, accessibility and governance. \n\nEstablish the required governance and control planes for structured and unstructured data interaction for AI systems. \nCollaborate with AI Engineers to ensure data structures support advanced AI capabilities.\nSupport the ongoing development of our Pathway platform and play a key role in the creation and ongoing delivery of AI agents across the end to end data lifecycle. (e.g. Data Governance & Data Quality Agents \")\nChallenge conventional approaches to discover breakthrough data solutions that unlock AI innovation for customers.\nRequired Skills & Experience:\nYou need to be equally adept at designing data driven platforms, as well as getting your fingers on key boards to build them. \nStrong experience with AWS data services with exposure to AI systems (e.g., AWS DataZone, Bedrock, Redshift, Glue) and/or Azure data services (e.g., Azure OpenSearch, Azure OpenAI, Fabric, Purview, Data Factory, Synapse)\n Proficiency with Python for data processing and pipeline development.\nExperience in building scalable andresilient data platforms in the public cloud. \n Data modelling and wrangling expertise to support advanced analytical use cases and ML, AI opportunities. \nExperience with containerisation technologies (Docker, Kubernetes) for scalable data solutions.\nExperience with vector databases and graph databases (e.g., Pinecone, Neo4j, AWS Neptune).\nUnderstanding of data mesh-fabric approaches and modern data architecture patterns.\nFamiliarity with AI/ML workflows and their data requirements.\nExperience with API specifications and data integrations acrossETL and streaming services (Glue, MSK, Kinesis, Kafka)\nFamiliarity with AI developer tools like Cursor and GitHub Copilot and desire to use them to 10x your throughput.\nCollaborative approach and excellent communication skills. \nStrong problem-solving abilities and creative thinking, with critical thinking credentials to solve complex business challenges across a range of industries. \nThe Mindset We Value:\nFrontier Thinking: We're looking for individuals who consistently ask \"what if?\" and aren't satisfied with the status quo. You should be excited about experimenting with emerging technologies and techniques that haven't yet been applied at enterprise scale.\nAdaptable Learning: The AI landscape evolves weekly. We need team members who thrive in this rapid change, constantly expanding their skills and adapting their approach as new capabilities emerge.\nClient Empathy: You must be able to translate complex technical concepts into value that resonates with business stakeholders, bringing them along on the AI transformation journey.\nSpeed with Purpose: We move fast, but always with clear intent. You should be comfortable working in rapid iterations while maintaining a focus on meaningful outcomes.\nGrowth Opportunities:\nExpand your expertise across multiple cloud platforms and emerging data technologies\nGain certification in cutting-edge AI, data and knowledge graph technologies\nWork directly with enterprise leadership to shape AI strategy\nDevelop deep specialisation in industry-specific solutions \nContribute to our thought leadership and IP development\nShape the future direction of our Pathway platform\nWe are just getting started, so you can play a key role in shaping the future of our business from the ground up. 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