At a Glance
- Tasks: Lead the design of innovative data products on the Databricks Lakehouse platform.
- Company: Join Cognizant, a global leader in tech and consulting.
- Benefits: Enjoy hybrid work, competitive salary, and professional growth opportunities.
- Other info: Collaborative environment with a focus on innovation and data democratization.
- Why this job: Shape the future of public sector data with cutting-edge technology.
- Qualifications: 10+ years in data architecture and strong Databricks expertise required.
The predicted salary is between 80000 - 100000 £ per year.
- 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.
About The Role
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.
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.
#J-18808-Ljbffr
Data Products Architect – Databricks employer: Cognizant
Cognizant is an excellent employer, offering a dynamic work culture that fosters innovation and collaboration within the UK Public Sector. Employees benefit from comprehensive growth opportunities, including training in cutting-edge AI technologies, while contributing to meaningful projects that impact government services. With a commitment to quality and excellence, Cognizant provides a supportive environment where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Data Products Architect – Databricks
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Cognizant!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Products Architect – Databricks at Cognizant.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Cognizant.
✨Apply Directly through Our Website
When you find a suitable opening like Data Products Architect – Databricks at Cognizant, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Products Architect – Databricks
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Cognizant, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cognizant. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cognizant
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cognizant!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
