Chief Data Architect

Job Overview

We are seeking a talented Data Architect to design and develop our data architecture and pipelines. Ideally someone who has worked on multiple projects with scalable and robust technologies.

The ideal candidate will need to be collaborative, organised, think out-of-the-box and be ready to pursue new opportunities in the field of healthcare.

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• Data Architecture Design: Develop and implement scalable and robust data architectures for data warehousing and enterprise data platforms.">
• Pipeline Development: Develop and optimise data pipelines and ETL/ELT/CDC workflows using tools such as Fivetran and Cloud Composer.">
• Collaboration: Collaborate with data scientists, product managers and business stakeholders to define data requirements and create logical and physical data models.">
• Database Administration: Manage and administer various database systems including BigQuery, SAP HANA and PostgreSQL.">
• Quality Assurance: Ensure data quality, integrity and security across all data platforms and pipelines.">
• Feature Store Design: Work with our AI/ML teams to design data serving layers and feature stores that support Vertex AI workloads.">
• Reporting Frameworks: Design and develop reporting frameworks and data marts to support business intelligence needs.">
• Integration: Integrate data platforms with various enterprise systems (CRMs, ERPs) and third-party APIs.">
• Data Governance: Define and implement data governance master data management and data cataloging strategies.">
• Full Data Lifecycle: Contribute to the full data lifecycle: requirements gathering architecture data modelling development testing and deployment.">
• Troubleshooting: Troubleshoot and resolve data platform issues to ensure high availability and optimal performance.">

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• Education: Bachelor's or Master's degree in Computer Science Software Engineering Data Science or a related field.">
• Programming Skills: Proficiency in one or more backend languages/frameworks with a strong preference for Python or Go.">
• API Design: Experience with building RESTful APIs and designing microservices for data delivery.">
• Data Modelling Fundamentals: Solid grasp of data modelling fundamentals including Kimball and Inmon methodologies.">
• SQL Proficiency: Proficiency in writing complex SQL queries and experience with SQL and NoSQL databases.">
• Data Warehousing Concepts: Familiarity with data warehousing concepts and best practices including CDC.">
• Version Control: Strong version-control habits Git and experience with CI/CD pipelines.">
• Communication Skills: Excellent problem-solving communication and collaboration skills.">
• Continuous Learning: Passion for continuous learning and adapting to emerging data technologies.">

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• Production-Grade Data Warehouses: Hands-on experience designing and deploying production-grade data warehouses.">
• Cloud Technologies: Deep experience with Google Cloud Platform GCP:">
• BigQuery: BigQuery for large-scale analytical workloads.">
• Cloud Composer: Cloud Composer for orchestrating complex data pipelines.">
• Vertex AI: Vertex AI for AI/ML model serving and feature stores.">
• Other Cloud Providers: Experience with other cloud providers AWS Azure and their data services.">
• Data Governance: Working knowledge of data governance frameworks master data management and data cataloging tools.">
• Experience with Ingestion Tools: Experience with data ingestion tools like Fivetran.">
• Business Intelligence Expertise: Business-intelligence expertise in building dashboards and reports with Power BI or Tableau.">
• Familiarity with Other Technologies: Familiarity with other data technologies such as SAP HANA.">
• Understanding of MLOps: Understanding of MLOps concepts and their application to data pipelines.">
• Open-Source Contributions: Contributions to open-source data projects or technical blogging/presentation">