QA Engineer Lead at Sanlam Group

Job Purpose:

• To transform software quality at Sanlam by building a modern, enterprise‑wide Quality Engineering capability that replaces manual testing with automation‑first, continuous quality practices.
• The role establishes a cluster‑wide Testing Guild, and applies cloud‑native, data‑ and AI‑assisted quality insights to accelerate delivery, improve platform resilience, and strengthen regulatory assurance - starting with Microsoft Dynamics 365 (CRM).

Role Requirements:

Output/Core Tasks:

Quality Engineering Strategy & Governance

• Define and lead Sanlam’s enterprise Quality Engineering (QE) strategy, setting standards, patterns and quality gates across the software delivery lifecycle
• Establish a cluster‑wide QE Guild to drive consistency, reuse, and skills uplift across CIO portfolios and product teams.
• Embed risk‑based quality governance, ensuring testing depth and evidence are proportionate to business, regulatory, and operational risk.
• Partner with Architecture, Security, Risk, and Compliance to ensure quality practices support regulatory assurance and audit readiness.

Automation‑First & Continuous Testing

• Drive the shift from manual testing to automation‑first, continuous quality practices embedded in CI/CD pipelines.
• Define and standardise test automation approaches across API, UI, integration, performance, security, and regression testing.
• Ensure testing is self‑service and developer‑enabled, with clear quality gates aligned to release and go/no‑go decisions.
• Improve key flow and reliability outcomes (e.g. defect escape, change failure rate, lead time for change).
• Institutionalize continuous testing practices (quality gates, dashboards, evidence, and test data strategies) to reduce time-to-market and incident risk.

Platform & Cloud‑Native Quality (Dynamics 365 Focus)

• Establish testing blueprints and standards for Microsoft Dynamics 365 (CRM), including: 
• Customisations and configurations
• Integration and API testing
• Security, role‑based access, and data integrity
• Regression and release validation
• Define environment and test‑data strategies to support cloud‑native and integration‑heavy architectures, including service virtualisation where required.
• Provide hands‑on quality leadership for priority CRM releases and programmes.

Data‑ and AI‑Assisted Quality Insights

• Introduce data‑driven quality analytics to provide visibility into release readiness, risk, and quality trends.
• Apply AI‑assisted testing techniques (e.g. customizations, integrations, security/roles, data quality, regression packs) with clear guardrails, change control, and auditability; start with lowrisk domains and scale as maturity grows.  
• Stand up quality analytics (flow metrics, defect economics, predictive risk signals) to inform release decisions and leadership reporting. 
• Translate quality signals into actionable insights for engineering leaders and CIO forums.

Capability Build & Operating Model

• Build and mature a QE Guild, including service offerings, standards, enablement, and communities of practice.
• Reduce reliance on external contractors by uplifting internal QE capability across squads and platforms.
• Define role profiles, learning paths, and career progression for QE, Software Development Engineer in Test, and automation engineers.
• Coach and influence engineering teams to treat quality as a shared responsibility, not a downstream activity.

Delivery Oversight & Risk Management

• Provide program level QA leadership for priority releases (esp. Dynamics CRM), ensuring coverage across functional, integration, performance, and security, with go/nogo criteria and quality signoffs.  
• Champion continuous improvement via postrelease analytics, production incident linkage, and defectescape/rootcause programs.
• Provide program level QA leadership for priority releases (esp. Dynamics CRM), ensuring coverage across functional, integration, performance, and security, with go/nogo criteria and quality signoffs.  
• Champion continuous improvement via post release analytics, production incident linkage, and defect escape/root cause programs.

What will make you successful in this role?

Experience

Essential:

• 8–12 years in QA/QE or software testing, with 3–5 years leading enterprise QA/QE or CoE functions.  
• Demonstrated success implementing automation first, continuous testing integrated with CI/CD (Azure DevOps or equivalent), including API/UI/contract/performance/security test stacks.  
• Strong background in cloud native testing (microservices, event driven, integration) and environment strategy (test data, virtualization, ephemeral envs).  
• Track record using quality analytics (DORA metrics, risk based prioritization, release readiness dashboards).  
• Proven experience implementing automation‑first testing using modern toolchains such as GitHub/GitHub Actions and/or Azure DevOps, and automation frameworks such as Playwright and/or Selenium with strong API testing capability (e.g., Postman or equivalent).

Advantageous

• Hands on experience with Microsoft Dynamics 365 (CRM) or similar enterprise CRM platforms (Salesforce), including customization/integration test strategies and UAT orchestration in Azure DevOps.  
• Familiarity with AI assisted testing and responsible AI guardrails in engineering workflows.  
• Exposure to reliability/operations practices (e.g., SRE concepts, quality gates, progressive delivery), aligning quality signals to release decisions.

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• Relevant certifications (preferred): 
• ISTQB Advanced/Test Manager or equivalent QE certification.
• Microsoft: Azure (e.g., AZ 400 DevOps Engineer, Azure Fundamentals/Administrator) to support Azure DevOps and cloud testing adoption.  
• AWS: Foundational/Associate/Professional or DevOps Engineering on AWS for cloud native test practices; AWS training on advanced testing in CI/CD. 
• Agile/SAFe or equivalent delivery credentials.

Competencies

Technical:

• Automation Engineering: Designs robust, scalable frameworks (API/UI/contract/perf/sec) with pipeline integration and test data strategies.  
• Continuous Testing & DevOps: Builds quality gates and traceability using Azure DevOps (Boards ↔ Repos ↔ Pipelines ↔ Test Plans). 
• Cloud Native Quality: Proficient in testing microservices, event streams, and integrations; leverages ephemeral environments and service virtualization.  
• AI Assisted QE & Analytics: Applies AI for test design/prioritization and maintenance with controls, audit trails, and value tracking; operationalizes quality metrics to inform release decisions.
• Dynamics 365 Testing: Defines CRM specific test strategies (security/roles, data model, integration flows) with end to end traceability for audits and UAT.  

Leadership:

• Strategic QE Transformation: Builds a TCoE and reduces contractor dependency through standards, enablement, and clear service catalogs.  
• Change Leadership & Influence: Shifts culture toward quality as a shared responsibility, partnering with CIOs, Product, Engineering, Architecture, and Security.  
• Talent Development: Grows internal SDET/QE capability; sets learning pathways (Azure DevOps, Dynamics, AI assisted testing, performance/security testing).  
• Outcome Focus: Uses objective quality signals to drive go/no go and reduce defect escape, change failure rate, and MTTR; ties quality to business outcomes.