Data Engineer

This team designs data assets and pipelines that deliver trusted, accurate data to Salesforce Marketing Cloud and Data360, giving CRM Architects, Specialist Client Engagement teams and Product Owners what they need to run targeted, data-driven campaigns and client journeys.

The work covers the full data lifecycle from approved Business Requirements Specifications (BRS) through architecture, development, testing and deployment of production-ready pipelines. The team makes sure data is reliable and actionable across every channel: in-app, WhatsApp, email, SMS and branch.

This team partners with Business Analysts, Product Owners and Marketing Managers to translate business decisions into deployable pipelines and support post-campaign measurement by publishing engagement data to the EDW and Kafka Topics for continuous improvement. Engineers in this team may be assigned across different workstreams depending on business needs, so you'll need to be as comfortable switching context as you are going deep.

At this level, you don't just build you shape how they build. You'll design the architecture, drive the engineering standard and bring less experienced engineers along with you. If you're ready to make decisions that reach millions of real clients across real channels, this is where you do it.

What you'll do

• Design, build and maintain robust, scalable and efficient data systems that meet the needs of our data environment
• Analyse business and system requirements to build and enhance data platforms at enterprise scale
• Drive architectural decisions providing input to the Data Architect on solution design for new and existing data flows
• Lead the design and development of complex new applications and systems
• Maintain data infrastructure reliability and efficiency across heterogeneous systems
• Mentor and develop less experienced engineers sharing knowledge and raising the engineering standard across the team

• Bachelor's Degree in Information Technology

• Honours Degree in Information Technology - Computer Science or Information Technology

• Expert-level SQL query optimisation, tuning and indexing strategies
• Architecture design for batch and streaming systems
• Deep knowledge of multiple programming languages including advanced algorithms for
• data processing
• Enterprise-wide real-time and batch data integration architecture design
• AWS deep knowledge of AWS data services and architecture (our team's primary cloud platform)
• Design and implementation of data lake, data warehouse or other data patterns
• Implementation of enterprise-wide data governance frameworks with automated quality and monitoring
• Ability to performance-optimise across heterogeneous systems
• Multi-environment GitOps strategy design including feature flags and advanced techniques
• Design and implementation of containerised data solutions using infrastructure as code
• CI/CD pipelines and Kubernetes design, configuration and implementation
• Design and configuration of enterprise workflow orchestration tools and pipelines

• At least 810 years of experience in data engineering
• Proven track record leading large-scale data engineering projects and driving measurable business impact
• Advanced to Expert level SQL and Python applied in production data engineering environments
• Advanced data engineering tools Apache Spark, Hadoop and similar
• Designing and implementing complex data architecture and infrastructure
• Aligning data engineering projects with business strategy and goals
• Providing data-driven recommendations to senior management and influencing decision-making
• Leading and mentoring engineers and data teams
• People development, knowledge sharing and training

• Salesforce Data Cloud experience here is an advantage, but not a requirement

• Clear criminal and credit record