Data Architect, Databricks

About the role

Red Badger is looking for a skilled Data Architect with strong Databricks expertise to join their growing team in Leeds. This role centers on designing and managing data architectures that power scalable analytics and engineering workflows across the organization. The Data Architect will partner with cross-functional teams to understand business objectives and translate them into effective data platform strategies. You will take ownership of the architectural vision for data infrastructure, ensuring it remains flexible, secure, and aligned with long-term organizational goals. This is an opportunity to shape how data flows through the company and influences decision-making at every level. Red Badger values technical excellence and encourages architects to stay current with evolving data technologies and industry trends.

Key facts

What you'll do

• Design and maintain scalable data architectures using Databricks as the primary analytics and engineering platform.
• Work closely with engineering and analytics teams to define data models, pipeline strategies, and integration patterns.
• Evaluate and recommend tools, frameworks, and technologies for data storage, processing, transformation, and governance.
• Lead the development of enterprise-grade data solutions that meet high standards for performance and reliability.
• Produce clear architectural documentation and diagrams that effectively communicate system design decisions to diverse stakeholders.
• Provide guidance and mentorship to junior data engineers and architects on Databricks-based workflow best practices.
• Assess existing data infrastructure and identify concrete opportunities for optimization, modernization, and improved efficiency.
• Ensure that all data pipelines remain secure, auditable, and fully compliant with organizational and regulatory policies.
• Collaborate with cloud platform teams to configure, manage, and optimize Databricks environments in production.
• Translate complex business requirements into detailed technical data architecture specifications that development teams can follow.
• Participate actively in code reviews and design reviews to uphold quality standards across the entire data platform.
• Coordinate with data governance and compliance teams to establish metadata management and comprehensive data lineage practices.
• Drive the adoption of data quality frameworks and monitoring practices across all data pipelines and assets.
• Engage with product teams to understand data needs and architect solutions that support evolving product requirements.

Requirements

• You have proven experience designing data architectures in large enterprise or similarly complex environments.
• Strong working knowledge of the Databricks platform including its core services and associated ecosystem of tools.
• Familiarity with major cloud platforms such as Azure, AWS, or GCP for data platform deployment and management.
• Hands-on experience with SQL and at least one general-purpose programming language for data engineering tasks.
• Solid understanding of data modeling techniques including dimensional modeling, relational modeling, and schema design principles.
• Ability to communicate technical architecture decisions and trade-offs clearly to both technical and non-technical audiences.
• Demonstrated track record of delivering data infrastructure projects on schedule and within defined scope and budget.
• A degree in computer science, engineering, or a related field, or equivalent practical hands-on experience.

Nice to have

• Experience with data governance frameworks and regulatory compliance requirements in production or enterprise settings.
• Familiarity with containerization technologies such as Docker or Kubernetes for orchestrating and managing data workloads.
• Background in real-time streaming data architectures and event-driven processing patterns for analytics applications.
• Exposure to data mesh or federated governance approaches within large-scale or distributed organizational structures.
• Knowledge of data lakehouse architectures and the ability to bridge traditional data warehousing with modern lakehouse patterns.

Skills & tools

• Databricks platform and Unity Catalog for data governance, access control, and asset management.
• Apache Spark for large-scale data processing, transformation, and distributed analytics workloads across clusters.
• SQL and Python for data engineering, analytics, and machine learning workflow development and automation.
• Cloud infrastructure services including Azure, AWS, or GCP for data platform deployment and operations.
• Data modeling tools and diagramming standards such as C4 or UML for architecture visualization.
• Version control systems like Git for infrastructure-as-code practices and collaborative configuration management.

Practical notes

• This position is based in Leeds and requires on-site presence at the Red Badger office on a regular basis.
• The hiring process includes multiple technical interviews focused on data architecture principles and system design exercises.
• Candidates should be prepared to discuss past projects involving Databricks deployment, data platform design, and infrastructure decisions.
• Red Badger values collaborative problem-solving, continuous improvement, and knowledge sharing as core parts of its engineering culture.