{"id":2148852,"url":"https://alion.io/job/cognizant-data-products-architect-databricks","title":"Data Products Architect – Databricks","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"B","score":76,"open_postings":86,"ghost_share":0,"stale_share":0.977,"repost_share":0,"time_to_fill_p50_days":24,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","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":75000,"max_usd":147000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":9},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"GDPR","optional":false},{"name":"IAM","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-23T14:35:20Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-13T01:38:56Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"Data Products Architect - Databricks\nThe Company\nCognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant has over 350,000 employees globally. Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 1000, and the Fortune 500, and is recognized among the fastest growing companies worldwide.\nData & AI Consulting - Public Sector\nCognizant’s Data & AI Consulting practice partners with government agencies and public sector organizations to modernize data ecosystems, establish trusted data foundations, and accelerate digital transformation through cloud-based data platforms, analytics, and AI solutions. Our teams help clients move beyond fragmented data landscapes by creating scalable, governed, and reusable data capabilities that enable enterprise-wide decision-making.\nThis role offers an opportunity to shape one of the most significant public sector data modernization programs in the UK, establishing a modern data product ecosystem on a Databricks Lakehouse platform that promotes data democratization, self-service consumption, and enterprise-wide reuse.\nAbout the Role\nAs a Data Products Architect - Databricks, you will lead the design and architecture of enterprise data products that enable trusted, reusable, and scalable data consumption across the organization. You will define the standards, governance frameworks, and architectural patterns that ensure data products are built once, managed consistently, and shared across multiple business domains.\nWorking closely with product owners, data engineers, platform architects, governance teams, and business stakeholders, you will help establish a modern data product operating model that supports self-service analytics, data sharing, and enterprise-wide innovation while maintaining strong governance and security standards.\nKey Responsibilities\nData Product Architecture & Design\nLead the architecture and design of enterprise data products built on the Databricks Lakehouse platform\nDefine and maintain standards, templates, and reference architectures that ensure data products are scalable, reusable, and interoperable\nDesign data products that are discoverable, versioned, self-describing, and aligned with data mesh and product-centric principles\nEstablish best practices for product design, schema management, metadata standards, lineage, and lifecycle governance\nEnsure data products are optimized for performance, scalability, reliability, and cost efficiency\nPromote consistency across product domains while enabling autonomy for data product teams\nSelf-Service Data Platform Enablement\nArchitect self-service data consumption capabilities that allow users to discover, access, and consume trusted data products independently\nDefine data contracts, service-level agreements, and access management frameworks for published data products\nCollaborate with platform teams to ensure the Databricks environment supports scalable self-service consumption patterns\nChampion the adoption of Unity Catalog as the enterprise governance and discovery layer\nDesign patterns that support data sharing, product consumption, and cross-domain interoperability\nEnable business and technical teams to leverage governed data assets through a consistent consumer experience\nSecurity, Governance & Compliance\nEnsure all data products comply with enterprise governance standards and public sector regulatory requirements\nDefine and implement data classification, access controls, auditability, and security controls across data products\nCollaborate with Cyber Security, Risk, and Data Governance teams to embed security-by-design principles into product delivery\nEnsure compliance with GDPR, Government Security Classifications, and other applicable regulatory frameworks\nEstablish governance processes that promote trust, quality, traceability, and effective stewardship of shared data assets\nTechnical Leadership & Standards\nServe as a senior technical authority for data product architecture across the program\nDefine architectural best practices for Delta Lake design, metadata management, product lifecycle governance, and data quality controls\nProvide architecture assurance and design reviews for data products developed by internal and third-party teams\nGuide architects, engineers, and analysts on the effective use of Databricks platform capabilities\nEvaluate emerging technologies, architectural approaches, and Databricks features to continuously improve the data product ecosystem\nEstablish reusable patterns and accelerators that support faster and more consistent delivery\nStakeholder Management & Advisory\nPartner with senior client stakeholders to understand business priorities and shape the enterprise data product strategy\nTranslate complex technical concepts into clear business-focused recommendations and architecture artefacts\nFacilitate workshops, governance reviews, and architecture discussions across business and technology teams\nCollaborate with product managers, engineers, analysts, and platform teams to align delivery with organizational objectives\nSupport strategic roadmap development for the continued evolution of data product capabilities\nSkills & Experience\nDomain Expertise\nStrong experience in data architecture, data product design, and enterprise data management\nDeep understanding of modern data platform architectures, data mesh principles, and product-based operating models\nExperience delivering large-scale data modernization and self-service analytics initiatives\nKnowledge of enterprise data governance, metadata management, and information architecture practices\nFamiliarity with public sector data management, governance, and compliance requirements\nFunctional Skills\nProven expertise in defining enterprise data product strategies, standards, and governance frameworks\nStrong experience establishing reusable product design patterns and operating models\nAbility to balance business needs with technical, governance, and operational requirements\nExperience designing data contracts, service models, and consumer engagement frameworks\nExcellent stakeholder management, communication, and consulting skills\nTechnical Skills\nDeep expertise in Databricks, including Lakehouse Architecture, Delta Lake, Unity Catalog, and Databricks SQL\nStrong understanding of data modelling, schema design, metadata management, and lineage tracking\nExperience implementing self-service data platforms and enterprise data catalog capabilities\nKnowledge of data mesh concepts and their practical implementation within large organizations\nExperience integrating Databricks with AWS services including S3, IAM, VPC, and AWS Glue\nFamiliarity with Apache Spark, dbt, data pipelines, and modern analytics architectures\nUnderstanding of access management, audit frameworks, and enterprise governance controls\nDelivery Experience\nExperience leading data product architecture across enterprise-wide data transformation programs\nProven track record delivering governed, reusable, and scalable data products within complex environments\nStrong collaboration across platform engineering, governance, analytics, and business teams\nExperience supporting data platform modernization, cloud migration, and large-scale transformation programs\nExperience working within UK Public Sector, Government, or other regulated industries preferred\nPersonal Attributes\nStrong communicator with the ability to engage effectively with both technical and non-technical audiences\nStrategic thinker able to design solutions that support long-term organizational goals\nAnalytical and solution-oriented mindset with strong problem-solving capabilities\nCollaborative leader capable of driving alignment across multiple stakeholder groups\nProactive and forward-looking, able to anticipate future data consumption and business needs\nAdaptable and resilient in complex, rapidly evolving environments\nContribution to Development of Practice\nContribute to Cognizant’s Data & AI Consulting capabilities in data products, governance, and modern data architecture\nDevelop reusable frameworks, methodologies, templates, and accelerators that support enterprise data product delivery\nSupport capability development, mentoring, and knowledge sharing across architecture and engineering communities\nContribute to thought leadership, white papers, proposals, and client advisory engagements focused on data mesh, self-service analytics, and data democratization\nPromote best practices in data governance, product ownership, and enterprise data strategy across client engagements\nIndustry Experience\n10+ years of experience in Data Architecture, Data Product Architecture, Information Architecture, or related disciplines\nProven experience designing and delivering enterprise data products on modern cloud-based data platforms\nExperience implementing self-service data ecosystems, data catalog solutions, and governed data-sharing models\nStrong experience working with Databricks and Lakehouse architectures at enterprise scale\nExperience working within UK Public Sector, Government, or highly regulated environments preferred\nFamiliarity with GDPR, Government Security Classifications, and public sector compliance requirements\nExperience supporting enterprise analytics, reporting, AI, and data-driven transformation initiatives\nCertifications (Preferred)\nDatabricks Certified Data Engineer Professional or equivalent Databricks certification\nAWS Certified Solutions Architect - Associate or Professional\nAWS Data Analytics Specialty Certification\nCertified Data Management Professional (CDMP) or equivalent\nRelevant cloud, governance, or architecture certifications\nLocation\nLondon, United Kingdom (Hybrid - London / Remote)\nSecurity Clearance: SC Clearance required or eligibility to obtain clearance.\nCogWW901","description_format":"text","description_chars":9973,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United 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