Data Engineer

About the Role

We're part of Client Engagement Delivery — the team that builds and maintains the data foundation powering our client engagement and campaign activity. We design 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.

Responsibilities

• 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

Requirements

• Bachelor's Degree in Information Technology
• At least 8–10 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

Preferred Qualifications

• 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
• Salesforce Data Cloud
• experience here is an advantage, but not a requirement
• Clear criminal and credit record