Data Engineer III

About the role:

We’re looking for a Data Engineer (L3) to own the evolution of our massive, cloud-native data platforms. This isn't about maintaining legacy pipelines; you’ll be leading high-stakes architectural design, specifically engineering for complex producer and consumer Redshift cluster environments on AWS. We operate at an incredible scale, running a powerhouse high-volume batch infrastructure while aggressively expanding our real-time footprint. Crucially, you'll help spearhead our shift toward adopting AI and agentic practices to build smarter, self-healing, and highly robust pipelines. Your design decisions will directly shape the data foundation for market-disrupting services and millions of banking clients. If you’re ready for high-autonomy, deep technical ownership, and systemic impact, let’s talk

Purpose Statement

To design, build, and optimise robust, scalable, and efficient data platforms and infrastructure that enable data-driven decision-making across the organisation. You will contribute to solution design, build and enhance data pipelines, and ensure the reliability, performance, and scalability of our data ecosystem.

What you'll be doing :

•    Design and build scalable data pipelines and data platforms (batch and streaming)
•    Develop high-performance data solutions using Python and advanced SQL (Redshift focus)
•    Contribute to solution design alongside Data Architects
•    Build and maintain cloud-based data infrastructure (preferably AWS)
•    Implement infrastructure as code (e.g., Terraform) and CI/CD practices
•    Work with Git, deployment pipelines, and SDLC processes
•    Design and optimise data lake, data warehouse, and integration patterns
•    Enable data quality, monitoring, and governance frameworks
•    Mentor and guide junior engineers and contribute to team capability building
•    Partner with stakeholders to translate business requirements into scalable data solutions

What we're looking for :

• Bachelor’s Degree in Information Technology or related field
• Proven experience in data engineering at scale (senior/staff level)
• Strong experience in:
  • Python
  • Advanced SQL (query optimisation, tuning, indexing – Redshift preferred)
  • Cloud platforms (AWS preferred)
• Experience with:
  • Data warehousing and data lake architectures
  • CI/CD, Git, and deployment practices
  • Infrastructure as code (e.g., Terraform)
  • Building and maintaining production-grade data pipelines
• Ability to work independently and contribute quickly in a complex environment
• Ideal / preferred:
  • Honours Degree in IT, Computer Science, or related field
• Experience with::
  o    Azure or GCP (with proven ability to transition to AWS)
  o    Power BI and Microsoft data stack exposure
  o    Real-time / streaming data architectures
  o    Workflow orchestration tools
  o    Containerised solutions
• Exposure to machine learning data pipelines or predictive analytics environments
• Leadership & team contribution
  • This is not a people management role, but you will:
    •    Provide technical mentorship and guidance to junior team members
    •    Help define frameworks, standards, and best practices
    •    Contribute to scaling and improving the engineering capability of the team
• We’re looking for someone who is:
  • Self-managed and accountable
  • Collaborative and team-oriented
  • Comfortable working in a fast-paced, evolving environment

Minimum Experience:

• A minimum of  8-10+ years’ experience in data engineering or related fields (aligned to staff-level capability)
  • Proven track record of:
    • Designing and delivering large-scale data solutions
    • Driving business impact through data platforms
    • Mentoring and developing other engineers

Education (Minimum)

Education (Ideal or Preferred)

Knowledge and Experience

Knowledge:

• Expert level SQL knowledge with query optimisation and tuning and indexing strategies.
  Architecture design for batch and streaming systems
• Deep knowledge of multiple programming languages and implementation of advanced algorithms for data processing.
• Design enterprise wide real-time / batch data integration architectures.
• Advanced knowledge of one cloud platforms data services.
• Design and implementation of data lake, data warehouse or other patterns.
  Implementation of enterprise-wide data governance frameworks with automated quality and monitoring.
• Ability to performance optimize across heterogeneous systems.
• Design of multi-environment GitOps strategies, that includes feature flags and other advanced techniques.
• Design & Implementation of containerized data solutions and infrastructure using infrastructure as code
• Design and configuration enterprise workflow orchestration tools and pipelines

Experience:

• Length of experience required is conditional on the qualifications obtained but must include:
• Proven track record of leading large-scale data engineering projects and driving business impact through data solutions 
• Experience with advanced data engineering tools and software (e.g., SQL, Python, Java, Apache Spark, Hadoop).
• Experience with machine learning algorithms and their application in predictive analytics 
• Experience in designing and implementing complex data architecture and infrastructure.
• With cloud computing platforms (e.g., AWS, Azure, Google Cloud) and their data services 2.
• Experience in aligning data engineering projects with business strategy and goals.
• Experience in providing data-driven recommendations to senior management and influencing decision-making.
• Experience in leading and mentoring less experienced engineers and data teams.
• In people development,  sharing and training.

Skills

Additional Information