Senior Data Engineer Consultant – Data Quality and Modern Cloud Platform
Senior Data Engineer Consultant builds and maintains secure, scalable cloud data platforms and pipelines, focusing on data quality, governance, and AI-ready foundations for clients.
- Compensation
- Not disclosed
- Location
- Durban, KZN, South Africa
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Nice to have
- Microsoft Fabric, Delta Lake and medallion architecture.
- Microsoft Purview or similar governance and lineage tools.
- Data-quality frameworks such as Great Expectations, Soda or dbt tests.
- Infrastructure as code (Bicep, Terraform or equivalent).
- Power BI semantic models and reporting-ready data products.
- SQL Server, T-SQL, SSIS, SSAS, SSRS and PowerShell in legacy or hybrid settings.
- API integration, event-driven or streaming architectures.
- Large-scale migration, reconciliation and cutover support.
- Experience in regulated data domains (customer, billing, banking and similar).
- Applied knowledge of generative AI, RAG, embeddings and vector stores.
Full description
Function: Data & Digital Consulting
Location: South Africa, hybrid / client-site as required
Reports to: Data Engineering or Consulting Practice Lead
About Keyrus
Keyrus is an internationally recognised specialist in Data and Digital, and a trusted partner to organisations across industries. We deliver practical business solutions using modern, scalable technologies, helping clients improve performance through data-enabled transformation.
We're passionate about innovation, teamwork and collective success, driven by exceptional people who combine technical depth with sound consulting judgement.
The Role
The Senior Data Engineer Consultant designs, builds and operationalises secure, scalable, governed data platforms for Keyrus clients. You'll turn business and data requirements into reliable ingestion, transformation, quality, storage and serving solutions that power reporting, analytics, migration and responsible AI use cases.
You'll work closely with data architects, business analysts, governance teams and client stakeholders, providing technical leadership, shaping solution architecture, supporting pre-sales and mentoring other engineers.
Key outcomes
- Secure, scalable, reliable and cost-conscious cloud data platforms and pipelines.
- Trusted, curated, reporting-ready data products with clear ownership and measurable quality.
- Repeatable profiling, cleansing, remediation, reconciliation and monitoring capabilities.
- Traceable metadata, lineage and transformation logic that support governance and sign-off.
- AI-ready data foundations and responsible use of AI-assisted engineering tools.
- Runbooks, knowledge transfer and a smooth transition into business-as-usual support.
What you'll be doing
Discovery and design
Assess client systems and data flows, document current-state architecture, and translate requirements into technical designs, mappings and delivery backlogs. Contribute to target-state lake, lakehouse and warehouse architecture, flag risks early, and explain trade-offs clearly to any audience.
Platform engineering
Build reusable ingestion, transformation and orchestration frameworks across databases, APIs, files, SaaS and streaming sources. Implement batch, incremental and CDC patterns with proper reconciliation, apply strong engineering practices (peer review, testing, CI/CD), and optimise SQL and Spark for performance and cost.
Data quality and remediation