Data Architect

Data Architect
Key Responsibilities

• Assess current data architecture and solutions
• Design target high-level data architecture and data management solutions for the TO BE data platform
• Design, develop and maintain data architectures that align with the organisation's strategic goals
• Recommend the best-fit technology components for the data platform in coordination with the Solution Architect
• Construct robust data pipelines to support scalable data ingestion, transformation and delivery
• Deploy integration system to collect data from various sources using real-time or batch ingestion technologies
• Establish data governance policies and procedures to ensure data quality, consistency, privacy, and compliance with relevant regulations
• Implement data security measures to safeguard sensitive information and ensure data is protected from unauthorized access or breaches
• Participate in product roadmap planning, recommending solutions
• Oversee the creation of data standards
• Develop a high-level description of entities and relationships through the conceptual data model
• Develop the conceptual data model which would be a representation of a data design to be implemented across all layers in data architecture
• Develop and implement data management policies, standards, and procedures
• Collaborate with client stakeholders to understand their data needs and requirements
• Lead and mentor junior architects and engineers, fostering a culture of technical excellence and continuous learning and innovation

Desired Experience and Qualifications

• Bachelor’s degree in computer science, information technology, or a related field (advanced degree such as master's or PhD in relevant area is a plus)
• Proven experience of at least 8+ years as a Data Architect with a focus on Data & AI Transformation Architecture
• Experience in building data pipelines with medallion (multi-hop) architectures
• In-depth knowledge of Data Management concepts and best practices
• Knowledge in industry-standard Enterprise Architecture Frameworks (e.g., TOGAF, Zachman).
• In-depth understanding of industry-standard data management maturity frameworks (i.e., DAMA-DMBOK, DCAM, CMMI CERT-RMM, IBM Data Governance Council, Stanford Data Governance, and Gartner’s Enterprise Information Management)

• Technical Expertise:
  
  • Programming Languages: High proficiency in Python, Java, Scala, and R.
  • Data Management & Databases: Oracle, SAP, SQL, NoSQL, and data warehousing solutions.
  • Big Data Technologies: Apache Hadoop, Spark, Kafka, and other big data tools.
  
  

Cloud Platforms:

• Microsoft Fabric
• Azure (Synapse Analytics, Databricks, Machine Learning, AI Search, Functions, etc.)
• Databricks on Azure
• AWS (S3, Redshift, SageMaker, etc.)
• Google Cloud Platform (BigQuery, Dataflow, etc.)

Data Governance:
Ab Initio, Informatica, Collibra, Purview, IBM InfoSphere, Great Expectations, Deepchecks, Databricks’ Unity Catalog, Delta Sharing, Catalog Explorer, Audit Logging, and Identity Management.

• Data Visualization: Matplotlib, Seaborn, Tableau, and Power BI.
• DevOps & MLOps: CI/CD principles, Docker, MLFlow, and Kubernetes.
• Strong knowledge of data modelling, database design, data integration and ETL processes
• Proficiency in SQL and NoSQL databases
• Proficiency in web technologies and languages 
• Relevant certifications (e.g., Azure or AWS Certified Solutions Architect, TOGAF, etc.) are a plus