Associate Data Architect

About Discovery 

Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society.

About Invest

Launched in 2007, Discovery Invest offers the full range of investment products for any client need, providing access to our top performing range of Discovery funds as well as a wide selection of leading local and international fund managers. Recently, Discovery Invest launched a unique offshore offering to enable South African investors unparalleled ease in accessing international investment opportunities. Discovery Invest is seeking to leverage the shared-value model to promote financial health and freedom for millions of South Africans. Through unique behavioural incentives and benefits, we reward clients for positive investment behaviour with extra investment returns. Discovery Invest is the only shared value investment platform in the country maximizing client outcomes before and after retirement. It is important for our employees to provide world class service to our internal and external clients, thereby ensuring long and sustainable relationships.

Key Purpose

The Data Architect is responsible for defining, designing, and governing the enterprise data architecture to enable scalable, secure, and high-performing data platforms.

This role provides architectural leadership across data engineering disciplines, ensuring efficient movement, storage, processing, and consumption of data across the enterprise. The Data Architect plays a critical role in enabling data-driven decision-making, advanced analytics, and digital experiences by delivering robust data platforms and data products.

The role requires deep collaboration with Data Engineers, Integration Architects, Security Architects, and Application Architects to ensure alignment across all architectural domains.

Key Outputs / Job Responsibilities may include but are not limited to:

• Data Architecture & Strategy:

• Define and maintain the enterprise data architecture strategy aligned to business objectives.
• Design scalable data platforms supporting batch, streaming, and real-time data processing.
• Establish architectural patterns for data pipelines, ingestion, transformation, storage, and consumption.
• Drive adoption of modern architectural paradigms such as:
  • Data Lakes, Data Warehouses, and Lakehouse architectures
  • Medallion (Bronze, Silver, Gold) data models
  • Data mesh / data product thinking

• Data Engineering Leadership:

• Lead and mentor Data Engineering teams across multiple initiatives.
• Provide oversight on delivery of data pipelines and platforms ensuring quality, performance, and scalability.
• Establish standards, frameworks, and best practices for:
  • Distributed data processing
  • Data pipeline orchestration
  • Data quality and testing.

• Data Processing & Pipelines

• Design and govern frameworks for:
  • Big data processing (Spark, PySpark)
  • Streaming architectures (Kafka, MSK, Debezium, Apache Flink)
  • Batch processing pipelines (Glue, Airflow)

• Ensure efficient and resilient data movement across platforms.
  • Define data lineage, observability, and traceability across pipelines.

• Data Storage & Modeling

• Architect and guide implementation of multiple data storage paradigms:
  • Relational databases
  • NoSQL (document, key-value, columnar)
  • Distributed storage systems
• Design optimized data models for different workloads:
  • OLTP systems
  • OLAP / Analytics platforms
  • Digital and real-time use cases (caching, APIs)

• Data Consumption & Optimization

• Define strategies for how different consumers access and use data:
  • Business intelligence and reporting
  • Advanced analytics and data science
  • API-based and digital channel consumption
• Architect data replication and synchronization strategies across target systems.
  • Ensure consistency and correctness of data across distributed stores.
  • Enable performant data access using techniques such as caching, indexing, and partitioning.

• Data Governance, Security & Compliance

• Establish and enforce data governance frameworks including:
  • Data catalogues and metadata management
  • Business ontology and semantic layers
• Ensure compliance with regulatory standards:
  • POPIA
  • GDPR

• Collaborate with Security Architects to implement:
  • Data security controls
  • Encryption, masking, and tokenization
  • Access control via IAM, PKI, OAuth
• Leverage AWS Lake Formation for centralized data governance, access control, and secure data sharing across the data platform.

• Data Products & Enablement

• Define and deliver data products for internal and external consumers.
• Drive standardization and reusability of data assets.
• Enable self-service data platforms for business users and partners.

• Stakeholder Collaboration

• Work closely with:
  • Business Architects (Requirements and Specifications)
  • Integration Architects (APIs, orchestration)
  • Security Architects (identity, encryption, governance)
  • Application Architects (application data needs)
• Facilitate alignment between business, engineering, and architecture teams.
• Present architectural solutions and ensure governance approvals.

• Technology & Platform Oversight

• Provide architectural governance across the data technology stack including:
  • AWS Cloud Services: S3, Glue, Athena, Redshift, IAM, Lake Formation
  • Big Data Processing: Apache Spark, PySpark
  • Streaming & Event Processing: Apache Kafka, Amazon MSK, Debezium, Apache Flink
  • Orchestration: Apache Airflow
  • Data Lake Technologies: Apache Iceberg
  • Analytics & BI: Amazon QuickSight, Python (Pandas)
  • Databases: Amazon DocumentDB, Redis
  • Containerisation & Compute: EKS (Kubernetes), Docker

• Ensure optimal use of cloud-native services, scalability, reliability, and cost efficiency.

Skills & Experience Required:

• Strong experience in enterprise data architecture and data engineering leadership.
• Deep understanding of:
• Data lifecycle (creation, storage, processing, consumption)
• Data pipeline design and distributed systems
• Proven experience with big data and streaming technologies (including Flink and Kafka ecosystems).
• Strong knowledge of data governance, compliance, and security frameworks.
• Expertise in multi-model databases and data storage paradigms.
• Ability to design scalable and resilient cloud-based data platforms (AWS preferred).
• Strong stakeholder engagement and communication skills.

Required Competencies

• Delivery Management: Expertise in leading complex, cross-functional projects from conception to completion within scope, time, and budget.
• Architectural Leadership: Ability to define and enforce enterprise-wide data architecture standards.
• Strategic Thinking: Align data architecture with long-term business outcomes.
• Collaboration & Influence: Work effectively across technical and business domains.
• Problem Solving: Design innovative solutions to complex data challenges.
• Governance & Compliance: Ensure adherence to regulatory and internal standards.
• Decision-Making: Make informed architectural decisions in complex environments.
• Continuous Improvement: Drive innovation and optimization in data platforms.

Education and Experience

Experience

• 8+ years in data engineering, data architecture, or related roles.
• Proven experience leading data engineering teams and large-scale data initiatives.
• Hands-on experience with cloud-based data platforms (preferably AWS).
• Strong track record in designing and implementing modern data architectures.
• Experience working in cross-functional enterprise environments.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
• Postgraduate qualification advantageous.
• Certifications (advantageous):

• • AWS Certified Solutions Architect / Data Analytics
  • TOGAF or similar architecture certification
  • Data engineering or big data certification

EMPLOYMENT EQUITY   
                             
The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.