Data Platform Architect
First seen by Alion on Aug 25, 2026.
Shift : UK Shift
Job Description :
We are looking for an experienced Data Platform Architect to lead the architecture and evolution of a modern, scalable Data Lakehouse ecosystem. This is a senior-level architecture role for professionals with strong experience in Data Lakehouse architecture, modern data platforms and open-source technologies, with the ability to define technical standards, drive architectural decisions and provide technical direction to engineering teams.
Key Responsibilities :
- Lead the architecture, design and modernization of enterprise-scale Data Lakehouse platforms.
- Define architecture across storage, compute, open-table formats, orchestration and data processing.
- Design decoupled and interoperable data platforms using open-source technologies while minimizing vendor lock-in.
- Establish standards for data pipelines, data modeling, CI/CD, coding practices and technical documentation.
- Design and oversee data governance, security, auditability and data quality frameworks.
- Drive platform performance, scalability, reliability and cost optimization.
- Conduct architecture and code reviews and provide technical guidance to senior engineering teams.
- Maintain Architectural Decision Records and communicate technical roadmaps, trade-offs and architectural decisions to senior stakeholders.
Required Skills & Experience :
- 13+ years of experience in Data Engineering, Data Architecture or Data Platform Architecture.
- 8+ years of experience in Data Architecture or Data Platform Architecture.
- 7+ years of experience in DBT and Kubernetes K8.
- Strong, hands-on experience designing, migrating or modernizing Data Lakehouse platforms in production environments.
- Strong experience with Databricks and/or Snowflake, particularly from an architecture and platform perspective.
- Strong hands-on experience with dbt Core for data transformation and modeling.
- Strong knowledge of Apache Iceberg and/or Delta Lake, including partitioning, optimization and schema evolution.
- Strong experience with Kubernetes and Docker for containerized data workloads.
- Advanced experience with Apache Airflow and production-grade data orchestration.
- Strong Python and/or PySpark experience.
- Strong understanding of AWS, Azure or GCP cloud ecosystems and storage-compute separation.
- Experience with data governance, DataOps and automated data quality frameworks.
- Ability to translate technical architecture, technical debt and roadmaps into business value for senior leadership.
Skills
Data Architect, Data Engineering, DataLake, Data Pipeline, Data Modeling, Data Build Tool, Snowflake DB, Azure Databricks, Apache Airflow, Python, AWS