Data Engineer

Orbis Investment Management Limited; City of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A global investment management firm is seeking a Full-Stack Data Engineer in London. You will design and maintain robust data solutions, ensuring data quality and integrity while supporting our investment decision-making processes. The ideal candidate has 3+ years of experience in data engineering, strong proficiency in Python and SQL, and the ability to collaborate with stakeholders. Join us for an exciting opportunity to work in a culture that values intellectual curiosity and growth.

Qualifications

• 3+ years of experience in software or data engineering.
• Strong proficiency in SQL, Python, and C#.
• Experience with data modeling, ETL pipelines, and data integration.

Responsibilities

• Design, build, and maintain reliable data pipelines and integrations.
• Contribute to the design and development of a new Snowflake-based data platform.
• Work directly with stakeholders to identify and resolve data issues.

Skills

SQL

Python

C#

Data modeling

ETL pipelines

Problem-solving

Communication

Tools

Snowflake

Dagster

Airflow

Job description

Data Engineer page is loaded## Data Engineerlocations: London Dorset Squaretime type: Full timeposted on: Posted Todayjob requisition id: JR439We are seeking a Full-Stack Data Engineer to join our London-based Investment Data team and help us onboard our next-generation data platform, while continuing to support and enhance our existing data systems. You will combine strong software engineering and data expertise to design, implement, and maintain robust data solutions that power the core data used in Orbis’ active investment decision-making process. You will work directly with stakeholders, data owners, and users to identify, troubleshoot, and resolve data issues, ensuring the platform and data products meet business needs. The successful candidate will be involved in migration, abstraction, and continued delivery on the current stack, while also building new data products and capabilities. You will also contribute to decisions about the technologies and architecture that will shape our future data platform.• Culture. We are committed to our Core Values. We encourage intellectual curiosity, individualism, and collaboration across different areas of the business. We seek to hear our people’s voices – whether quiet or loud. Sharing ideas and challenging the status quo are commonplace. • Impact. Your work directly supports Orbis’ investment process and decision-making. • Autonomy and accountability. While guidance and support are provided, team members are responsible for their own work. • Growth opportunities. We support our people in continuous learning and development. • Agile environment. We are committed to providing a work environment that balances the needs of our clients, the needs of our teams, and the personal needs, commitments, and interests of our people. • Philanthropy. Our people can contribute to society in a unique and personal way, through various philanthropy opportunities and programmes.• Design, build, and maintain reliable data pipelines and integrations using Python, SQL, and C#. • Contribute to the design and development of a new Snowflake-based data platform, helping decide which technologies and architectures best serve our long-term goals. • Support, maintain, and enhance existing systems as part of a long-term migration strategy. • Migrate and refactor legacy solutions to integrate with the data platform. • Work directly with stakeholders, data owners, and users to identify, diagnose, and resolve data-related issues. • Maintain high standards of data quality, integrity, and operational reliability and document this robustly. • Engage hands-on with data – profiling, cleaning, and transforming as needed to support analysis and reporting. • Collaborate across teams to ensure consistent, efficient, and high-quality data flows and engineering with a continued focus on what’s best for the long-term success of the organisation in delivering client and investment alpha. **About You** You are a pragmatic, hands-on engineer who enjoys solving complex data problems and building robust systems that scale. You are comfortable operating in a hybrid environment, balancing new platform work with ongoing support, and can collaborate effectively with both technical and non-technical stakeholders, including defining requirements.**Required Skills & Experience:** • 3+ years of experience in software or data engineering. • Strong proficiency in SQL, Python, and C# (including query optimisation and performance tuning). • Experience with data modelling, ETL pipelines, and data integration. • Proven ability to work directly with stakeholders and data users to understand problems and deliver effective solutions. • Strong analytical and problem-solving skills with a structured, methodical approach. • Excellent communication and collaboration abilities.**Preferred Experience:** • Building or migrating to Snowflake (or other cloud-based) data platforms. • Familiarity with Dagster, Airflow, or similar orchestration tools. • Experience managing the transition between legacy and modern data systems. • Exposure to financial data or prior work with market data systems. Familiarity with financial datasets is particularly valuable for ongoing operations and resolving data issues. • Experience delivering innovative and proof-of-concept work projects. • Experience working with AI tools and exposing data for consumption by AI tools.**Instructions for application** To complete your application, please submit your resume.**The Company** We are a global firm with offices across eight countries, over 400 employees and more than $40 billion in assets under management. But those numbers don’t define Orbis. It’s our values, the way we do things day by day, and the value we add for our clients that define us. Our investment philosophy is fundamental, long-term and contrarian. As contrarian investors, we strive to adopt a different perspective, which informs every aspect of our approach. To invest differently, you need to think differently. This is encouraged by having teams of people with different backgrounds, experiences and ways of thinking.