Description:
We are seeking a highly skilled Senior Data Engineer to lead the design, development, and optimisation of enterprise data infrastructure. The ideal candidate will bring a strategic mindset, strong technical expertise, and leadership capabilities to drive the creation of scalable data solutions aligned with business goals.
This position requires someone with hands-on experience in data architecture, pipeline automation, and team leadership. You will work closely with cross-functional teams, guiding efforts in data modelling, analytics, and business intelligence.
Key Responsibilities
Data Architecture and Solution Design
Lead the design, development, and implementation of scalable data solutions. Use Wherescape to build and automate data pipelines for efficient data ingestion and transformation. Architect maintainable data systems that align with business and technical requirements. Analyse performance and implement improvements based on feedback and best practices.
Governance and Data Quality
Ensure high standards of data quality, accuracy, and consistency. Enforce metadata management, data lineage, and governance policies. Develop validation and control mechanisms across all data sources.
ETL Development and Automation
Design and manage end-to-end ETL processes using Wherescape and other tools. Optimise workflows and troubleshoot processing issues. Implement scheduling, monitoring, and alerting to ensure data availability and integrity.
Collaboration and Mentorship
Work with Data Scientists, Analysts, and BI teams to align data strategy with analytics needs. Partner with cross-functional stakeholders to resolve data issues. Mentor junior data engineers and support knowledge sharing across the team.
Minimum Requirements
Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field. 8+ years of experience in data engineering or related roles.
Technical Skills (Non-negotiable)
Expert SQL skills Hands-on experience with Cloudera Strong knowledge of Data Vault modelling methodology Solid experience with data warehouse architecture and design. Strong command of Python and/or Java. Familiarity with big data ecosystems: Hadoop, Spark, Kafka. Experience with ETL tools (especially Wherescape), SAP HANA, and scheduling tools (e.g., Automic). Understanding of both Kimball and Data Vault data modelling patterns.
Leadership and Communicatio