Databricks Platform Solutions Architect

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Role: Databricks Architect

Job Type: Permanent

Location: Reading, UK / Hybrid

Number of hours: 40 hours per week – full time

Ready to apply your Databricks expertise to architect scalable, modern data platforms?

We have an exciting role for you –
Databricks Architect.

Careers at TCS:
It means more

TCS is a purpose‑led transformation company, built on belief. We do not just help businesses to transform through technology. We support them in making a meaningful difference to the people and communities they serve - our clients include some of the biggest brands in the UK and worldwide. For you, it means more to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership.

• Build strong relationships with a diverse range of stakeholders.
• Gain access to endless learning opportunities.
• Work closely with the range of teams within the business to bring products to life.

As a Databricks Architect you will be responsible for design, develop, and governing the organization’s data landscape, ensuring data assets are managed as a strategic resource. Creating and maintaining robust, scalable, and secure data models, data flows, and data architecture standards (including databases, data warehouses, data lakes, and streaming platforms) to support critical business objectives, analytics, reporting, and regulatory compliance.

• Design secure and scalable data warehouses and lakehouse architectures, implementing strong data quality and governance frameworks.
• Design, monitor and optimise data pipelines using Databricks, ensuring performance, scalability and reliability.
• Collaborate closely with data scientists, business analysts and Dev Ops teams to deliver end‑to‑end platform solutions.
• Build ETL/ELT pipelines using Azure Databricks, enabling seamless integration with multiple data sources.
• Lead greenfield implementations of the Lakehouse framework.
• Work with Azure Data Lake, Azure Data Factory, and cloud storage services.
• Implement robust partitioning, clustering and optimisation strategies.
• Define and select the appropriate data modelling approach for each use case.
• Establish data governance and security requirements in line with organisational standards.
• Analyse and define enterprise data architecture frameworks, including security, metadata, master data and reference data.
• Present design solutions for architectural review and approval.
• Maintain a holistic view of enterprise data landscapes and align architecture with organisational strategy.
• Develop and implement data management, archiving and housekeeping standards.
• Drive enhancements to improve performance, stability and usability of data products.
• Contribute to coding tasks using PySpark and SQL/Python Spark.
• Support CI/CD and Dev Ops processes, including Git‑based version control.

• Experience designing ETL/ELT flows and building pipelines using Azure Databricks.
• Hands‑on experience with Azure Data Lake, Azure Data Factory, and integrating multiple source systems.
• Strong experience implementing Lakehouse architecture in greenfield environments.
• Expertise in data modelling, including conceptual, logical and physical models.
• Strong understanding of data governance, security standards, and compliance requirements.
• Experience designing enterprise data frameworks covering security, metadata, reference and master data.
• Ability to present designs to architectural forums and secure approvals.
• Strong awareness of organisational cloud roadmaps and ability to align architecture accordingly.
• Experience supporting enterprise data landscapes and implementing data management strategies.
• Experience driving platform improvements and enhancements.
• Strong stakeholder‑management and communication skills.
• Ability to articulate customer requirements, risks and impacts effectively.
• Experience collaborating with large project teams in Agile delivery environments.
• Experi…