Cognizant
Data Platform Architect – Databricks (AWS)
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Data Platform Architect – Databricks (AWS)
The Company
Cognizant (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.
Data & AI Consulting – Public Sector
Cognizant’s Data & AI Consulting practice partners with government agencies and public sector organizations to modernize data ecosystems, accelerate cloud adoption, and unlock value through trusted, data-driven decision making. Our teams help clients establish secure, scalable, and governed data platforms that support enterprise-wide analytics, artificial intelligence, and digital transformation initiatives.
This role offers the opportunity to help shape one of the most significant public sector data modernization programs in the UK, establishing a Databricks-based Lakehouse platform on AWS that will become the strategic foundation for future data and analytics capabilities.
About The Role
As a Data Platform Architect – Databricks (AWS), you will lead the architecture and design of a modern enterprise data platform built on Databricks and AWS. You will define the foundational architecture, governance standards, security controls, integration patterns, and operational frameworks that enable scalable, secure, and self-service data capabilities across the organization.
Working closely with data engineers, cloud architects, platform teams, cybersecurity stakeholders, and program leadership, you will establish the technical direction of the platform and ensure it supports both current and future business needs.
Key Responsibilities
Platform Architecture & Design
- Lead the end-to-end architecture and design of the Databricks Lakehouse platform on AWS
- Define foundational architecture components including landing zones, medallion architecture (Bronze, Silver, Gold), storage architecture, and compute strategies
- Establish scalable platform standards, frameworks, and engineering patterns to support enterprise-wide data initiatives
- Design platform capabilities that support both batch and real-time streaming workloads
- Define data access, consumption, and serving patterns that enable trusted and governed self-service analytics
- Ensure platform architecture is aligned with enterprise data strategy and long-term modernization objectives
AWS Infrastructure & Integration
- Design and govern the AWS infrastructure supporting the Databricks platform, including networking, security, storage, and identity architecture
- Define integration patterns with internal systems and AWS services including S3, Glue, Kinesis, EventBridge, and related data services
- Establish infrastructure-as-code standards using Terraform or equivalent tooling
- Collaborate with DevOps and Cloud Engineering teams to implement automated deployment and configuration management practices
- Ensure platform scalability, resiliency, performance, and operational efficiency across environments
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Security, Governance & Compliance
- Embed security-by-design principles into all platform architecture decisions
- Lead the implementation and governance of Unity Catalog, including metastore design, workspace governance, and access control frameworks
- Ensure compliance with public sector security requirements, GDPR, and applicable regulatory frameworks
- Define platform-wide monitoring, observability, audit logging, and alerting capabilities
- Collaborate with Cyber Security, Risk, and Data Governance teams to establish enterprise governance controls and operational guardrails
Technical Leadership & Standards
- Serve as the senior technical authority for the Databricks platform architecture
- Establish engineering best practices covering Delta Lake design, workload orchestration, compute optimization, and cost management
- Provide technical assurance across platform implementation activities delivered by internal teams and external partners
- Define reusable architecture patterns, standards, and accelerators that improve consistency and delivery quality
- Continuously evaluate emerging Databricks and AWS capabilities and recommend innovative platform enhancements
Stakeholder Management & Advisory
- Engage with senior client stakeholders, program leadership, and governance boards to communicate architecture decisions and technical strategy
- Translate complex architecture concepts into clear and business-friendly communications
- Facilitate architecture reviews, technical workshops, and design governance sessions
- Build strong relationships across business, engineering, security, cloud, and operational teams
- Support strategic planning and roadmap development for future platform evolution
Skills & Experience
Domain Expertise
- Strong experience designing and implementing enterprise-scale data platforms and modern Lakehouse architectures
- Deep understanding of data modernization strategies, cloud-native data ecosystems, and enterprise analytics platforms
- Experience delivering large-scale data transformation programs within public sector or regulated industries
- Knowledge of enterprise data governance, security, and compliance principles
Functional Skills
- Proven ability to lead architecture design and technical decision-making across complex data programs
- Strong expertise in architecture standards, governance frameworks, and solution assurance processes
- Ability to define scalable operating models and platform governance structures
- Excellent communication, stakeholder engagement, and consulting capabilities
- Experience translating business requirements into strategic platform architecture solutions
Technical Skills
- Deep expertise in Databricks, including Lakehouse Architecture, Delta Lake, Unity Catalog, Workflows, and cluster management
- Strong experience designing cloud-native data platforms on AWS
- Hands-on knowledge of AWS services including S3, IAM, VPC, Glue, Kinesis, EventBridge, and CloudWatch
- Strong understanding of medallion architecture, large-scale data lake implementations, and data engineering patterns
- Experience with Infrastructure-as-Code tools such as Terraform
- Knowledge of DevOps, CI/CD, platform automation, and cloud-native operational practices
- Familiarity with Apache Spark, dbt, and modern data integration technologies
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Delivery Experience
- Experience leading architecture for enterprise-wide Databricks implementations and cloud data modernization initiatives
- Proven success delivering scalable and secure data platforms in complex environments
- Experience collaborating with cross-functional teams including cloud engineering, cybersecurity, operations, and governance functions
- Experience supporting greenfield platform builds, legacy modernization programs, and large-scale migrations
- Experience working within UK Public Sector, Government, or other highly regulated environments preferred
Personal Attributes
- Strong communicator with the ability to engage effectively at both technical and executive levels
- Strategic thinker who balances immediate delivery requirements with long-term platform vision
- Analytical and solution-oriented mindset with strong problem-solving capabilities
- Collaborative leader who can align diverse stakeholder groups around shared architectural goals
- Proactive and forward-looking, with an ability to identify risks, dependencies, and opportunities early
- Adaptable and resilient in fast-paced transformation environments
Contribution to Development of Practice
- Contribute to Cognizant’s Data & AI Consulting capabilities in cloud data platforms and Databricks architecture
- Develop reusable platform blueprints, reference architectures, governance models, and accelerators
- Support knowledge sharing, mentoring, and capability development within the architecture community
- Contribute to thought leadership, proposals, client workshops, and innovation initiatives related to Databricks, AWS, and modern data platforms
- Promote engineering excellence and architecture best practices across client engagements
Industry Experience
- 10+ years of experience in Data Platform Architecture, Data Architecture, Cloud Architecture, or related disciplines
- Proven experience delivering enterprise Databricks implementations and Lakehouse architecture solutions
- Extensive experience designing cloud-native data platforms on AWS
- Experience working within UK Public Sector, Government, or regulated industries strongly preferred
- Familiarity with Government Security Classifications, GDPR, and public sector governance frameworks
- Demonstrated experience supporting enterprise-scale analytics, reporting, and AI-enabled data ecosystems
Certifications (Preferred)
- Databricks Certified Data Engineer Professional or equivalent Databricks certification
- AWS Certified Solutions Architect – Associate or Professional
- AWS Data Analytics Specialty Certification
- Terraform Associate Certification
- Relevant cloud, security, or platform engineering certifications
Location
London, United Kingdom (Hybrid – London / Remote)
Security Clearance
SC Clearance required or eligibility to obtain clearance.
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