Senior Data Engineer

About the role

The Family Office, an independent wealth management firm serving high-net-worth individuals and families, is seeking a Senior Data Engineer. The role designs, builds and optimises scalable data platforms supporting business intelligence, analytics, AI and data-driven decisions. It covers data pipelines, data infrastructure, data quality and integration of data from many sources.

Key responsibilities

• Data engineering and architecture: design, develop and maintain scalable data pipelines and integration solutions; build and optimise data lakes, data warehouses and data marts; design batch and real-time processing frameworks; design data models for reporting, analytics and machine learning; set best practices for data architecture, governance and security.
• Data platform management: manage and optimise cloud-based data platforms, monitor performance, reliability and availability, ensure data quality and integrity, and implement automated validation and monitoring.
• Analytics and business enablement: work with stakeholders, analysts and data scientists on data requirements, deliver datasets for dashboards and reporting, and support AI and machine learning initiatives.
• Development and automation: build and maintain ETL/ELT workflows, automate ingestion and transformation, implement CI/CD for data projects, and optimise database performance and query efficiency.
• Leadership and collaboration: mentor junior data engineers, collaborate with technology, product and business teams, and take part in architecture reviews and technology evaluations.

Required profile

• Bachelor's degree in computer science, Data Engineering, Information Systems or a related field.
• 5-8+ years of experience in data engineering or related roles.
• Hands-on experience building and managing large-scale data pipelines and with data warehousing solutions.
• Experience with cloud platforms such as AWS, Azure or Google Cloud.

Required skills

• Strong proficiency in SQL and Python.
• Strong understanding of data modelling and database design.
• ETL/ELT workflows, data warehousing, and cloud data platforms.