We are hiring for Technical Data Architect location: Central London Type : Permanent Hybrid role (2-3 days from client location) We are seeking a highly skilled TechnicalData Architect- with expertise in Databricks, PySpark, and modern data engineering practices. The ideal candidate will lead the design, development, and optimization of scalable data pipelines, while ensuring data accuracy, consistency, and performance across the enterprise Lakehouse platform. This role requires strong leadership, technical depth, and the ability to collaborate with cross-functional teams. ________________________________________ Key Responsibilities Lead the design, development, and maintenance of scalable, high-performance data pipelines on Databricks. Architect and implement data ingestion, transformation, and integration workflows using PySpark, SQL, and Delta Lake. Guide the team in migrating legacy ETL processes to modern cloud-based data pipelines. Ensure data accuracy, schema consistency, row counts, and KPIs during migration and transformation. Collaborate with Data engineer, BI Engineers, and Security teams to define data standards, governance, and compliance. Optimize Spark jobs and Databricks clusters for performance and cost efficiency. Support real-time and batch data processing for downstream systems (e.g., BI tools, APIs, reporting consumers). Mentor junior engineers, conduct code reviews, and enforce best practices in coding, testing, and deployment. Validate SLAs for data processing and reporting, ensuring business requirements are consistently met. Stay updated with industry trends and emerging technologies in data engineering, cloud platforms, and analytics. ________________________________________ Required Skills & Qualifications 10-12 years of experience in data engineering, with at least 3 years in a technical lead role. Strong expertise in Databricks, PySpark, and Delta Lake. DBT Advanced proficiency in SQL, ETL/ELT pipelines, and data modelling. Experience with Azure Data Services (ADLS, ADF, Synapse) or other major cloud platforms (AWS/GCP). Strong knowledge of data warehousing, transformation logic, SLAs, and dependencies. Hands-on experience with real-time streaming near-realtime batch is a plus., optimisation of data bricks and DBT workload and Delta Lake Familiarity with CI/CD pipelines, DevOps practices, and Git-based workflows. Knowledge of data security, encryption, and compliance frameworks (GDPR, SOC2, ISO ).good to have Excellent problem-solving skills, leadership ability, and communication skills. ________________________________________ Preferred Qualifications Certifications in Databricks, Azure good to have Experience with DBT, APIs, or ( BI integrations (Qlik, Power BI, Tableau).- good to have )