Data Products Architect – Databricks

Data Products Architect – Databricks 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, 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.

This 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. About the Role

As 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.

Working 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. Key Responsibilities Data Product Architecture & Design

Lead the architecture and design of enterprise data products built on the Databricks Lakehouse platform

Define and maintain standards, templates, and reference architectures that ensure data products are scalable, reusable, and interoperable

Design data products that are discoverable, versioned, self-describing, and aligned with data mesh and product-centric principles

Establish best practices for product design, schema management, metadata standards, lineage, and lifecycle governance

Ensure data products are optimized for performance, scalability, reliability, and cost efficiency

Promote consistency across product domains while enabling autonomy for data product teams Self-Service Data Platform Enablement

Architect self-service data consumption capabilities that allow users to discover, access, and consume trusted data products independently

Define data contracts, service-level agreements, and access management frameworks for published data products

Collaborate with platform teams to ensure the Databricks environment supports scalable self-service consumption patterns

Champion the adoption of Unity Catalog as the enterprise governance and discovery layer

Design patterns that support data sharing, product consumption, and cross-domain interoperability

Enable business and technical teams to leverage governed data assets through a consistent consumer experience Security, Governance & Compliance

Ensure all data products comply with enterprise governance standards and public sector regulatory requirements

Define and implement data classification, access controls, auditability, and security controls across data products

Collaborate with Cyber Security, Risk, and Data Governance teams to embed security-by-design principles into product delivery

Ensure compliance with GDPR, Government Security Classifications, and other applicable regulatory frameworks

Establish governance processes that promote trust, quality, traceability, and effective stewardship of shared data assets Technical Leadership & Standards

Serve as a senior technical authority for data product architecture across the program

Define architectural best practices for Delta Lake design, metadata management, product lifecycle governance, and data quality controls

Provide architecture assurance and design reviews for data products developed by internal and third-party teams

Guide architects, engineers, and analysts on the effective use of Databricks platform capabilities

Evaluate emerging technologies, architectural approaches, and Databricks features to continuously improve the data product ecosystem

Establish reusable patterns and accelerators that support faster and more consistent delivery Stakeholder Management & Advisory

Partner with senior client stakeholders to understand business priorities and shape the enterprise data product strategy

Translate complex technical concepts into clear business-focused recommendations and architecture artefacts

Facilitate workshops, governance reviews, and architecture discussions across business and technology teams

Collaborate with product managers, engineers, analysts, and platform teams to align delivery with organizational objectives

Support strategic roadmap development for the continued evolution of data product capabilities Skills & Experience Domain Expertise

Strong experience in data architecture, data product design, and enterprise data management

Deep understanding of modern data platform architectures, data mesh principles, and product-based operating models

Experience delivering large-scale data modernization and self-service analytics initiatives

Knowledge of enterprise data governance, metadata management, and information architecture practices

Familiarity with public sector data management, governance, and compliance requirements Functional Skills

Proven expertise in defining enterprise data product strategies, standards, and governance frameworks

Strong experience establishing reusable product design patterns and operating models

Ability to balance business needs with technical, governance, and operational requirements

Experience designing data contracts, service models, and consumer engagement frameworks

Excellent stakeholder management, communication, and consulting skills Technical Skills

Deep expertise in Databricks, including Lakehouse Architecture, Delta Lake, Unity Catalog, and Databricks SQL

Strong understanding of data modelling, schema design, metadata management, and lineage tracking

Experience implementing self-service data platforms and enterprise data catalog capabilities

Knowledge of data mesh concepts and their practical implementation within large organizations

Experience integrating Databricks with AWS services including S3, IAM, VPC, and AWS Glue

Familiarity with Apache Spark, dbt, data pipelines, and modern analytics architectures

Understanding of access management, audit frameworks, and enterprise governance controls Delivery Experience

Experience leading data product architecture across enterprise-wide data transformation programs

Proven track record delivering governed, reusable, and scalable data products within complex environments

Strong collaboration across platform engineering, governance, analytics, and business teams

Experience supporting data platform modernization, cloud migration, and large-scale transformation programs

Experience working within UK Public Sector, Government, or other regulated industries preferred Personal Attributes

Strong communicator with the ability to engage effectively with both technical and non-technical audiences

Strategic thinker able to design solutions that support long-term organizational goals

Analytical and solution-oriented mindset with strong problem-solving capabilities

Collaborative leader capable of driving alignment across multiple stakeholder groups

Proactive and forward-looking, able to anticipate future data consumption and business needs

Adaptable and resilient in complex, rapidly evolving environments Contribution to Development of Practice

Contribute to Cognizant’s Data & AI Consulting capabilities in data products, governance, and modern data architecture

Develop reusable frameworks, methodologies, templates, and accelerators that support enterprise data product delivery

Support capability development, mentoring, and knowledge sharing across architecture and engineering communities

Contribute to thought leadership, white papers, proposals, and client advisory engagements focused on data mesh, self-service analytics, and data democratization

Promote best practices in data governance, product ownership, and enterprise data strategy across client engagements Industry Experience

10+ years of experience in Data Architecture, Data Product Architecture, Information Architecture, or related disciplines

Proven experience designing and delivering enterprise data products on modern cloud-based data platforms

Experience implementing self-service data ecosystems, data catalog solutions, and governed data-sharing models

Strong experience working with Databricks and Lakehouse architectures at enterprise scale

Experience working within UK Public Sector, Government, or highly regulated environments preferred

Familiarity with GDPR, Government Security Classifications, and public sector compliance requirements

Experience supporting enterprise analytics, reporting, AI, and data-driven transformation initiatives Certifications (Preferred)

Databricks Certified Data Engineer Professional or equivalent Databricks certification

AWS Certified Solutions Architect – Associate or Professional

AWS Data Analytics Specialty Certification

Certified Data Management Professional (CDMP) or equivalent

Relevant cloud, governance, or architecture certifications Location

London, United Kingdom (Hybrid – London / Remote)

Security Clearance: SC Clearance required or eligibility to obtain clearance.