Data Architect

Role & Responsibilities

• Possess 15 plus years of work experience at a reputable Data & AI services firm.
• Outstanding written and verbal communication skills, with a flair for compelling storytelling.
• Lead the end-to-end architectural design for the enterprise data and analytics platform across Azure.
• Design scalable data ingestion, transformation, and orchestration solutions using Azure Data Factory (ADF) and Databricks.
• Collaborate closely with the UK Data Science team to understand analytical requirements, model needs, and integration patterns for AI/ML workloads

You Must Posses

• Possess a Bachelor or master’s degree in IT, Computer Science, Engineering, Business, or Decision Sciences.
• Drive meaningful customer conversations and achieve positive business outcomes.
• Proven experience as a Technical Architect, Data Architect, or Lead Data Engineer in large enterprise environments.
• Strong knowledge of insurance domain processes, including policy, claims, underwriting, pricing, risk, and regulatory reporting.
• Hands-on expertise with:
• Azure Data Factory (ADF) for pipeline orchestration
• Databricks (PySpark, Delta Lake, MLflow) for data engineering and ML integration
• Azure ecosystem (Key Vault, Data Lake, Synapse, Functions, Logic Apps)
• Strong understanding of AI/ML lifecycle, model operationalization, and integration with enterprise data platforms.
• Experience creating architecture standards, guardrails, governance frameworks, and engineering best practices.
• Deep technical knowledge of data architecture, integration patterns, CI/CD for data, pipeline monitoring, and data quality frameworks.
• Excellent stakeholder management and communication skills, particularly with Data Science teams and business leaders.
• Strong documentation and solutioning skills, capable of producing high-quality architectural blueprints.
• Strong understanding of data governance, metadata management, and data lineage.
• Proficiency in SQL for advanced data modelling, optimization, and validation.
• Excellent ability to translate business requirements into technical designs.
• Strong problem-solving and analytical thinking skills.
• Understanding of the Agile methodology for development and execution.
• Maintains an active learning approach, staying current with industry trends, and applying these insights to develop solutions, initiate new projects, and shape capability roadmaps.
• Contribute to the development of solutions and automation accelerators and mentor emerging Data & AI talent.
• Adept at recruiting top-tier Data & AI practitioners.