Data Engineer

Data Engineer

We are seeking a 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 data 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.

Design, build, and maintain reliable data pipelines and integrations using Python, SQL, Dagster, Snowflake, dbt and C#, leveraging agentic AI tooling. 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. Coach, train, and mentor less experienced team members. Work with business analysts and stakeholders to gather and translate requirements into technical specifications. 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, scalable systems. 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: 5+ years of experience in data engineering. Strong proficiency in SQL, Python, and Snowflake (including query optimisation and performance tuning). Experience with data modelling, ELT pipelines, and data integration. Proven ability to work directly with stakeholders and data users to understand problems and deliver effective solutions. Experience with enabling others through technical leadership, including mentoring, coaching, and training. 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. Supporting SQL Server solutions, including administration 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. Experience working with dbt and C#.