Data Engineer – Investment Management / Asset Management
Salary: £80,000 to £110,000 per annum Plus Bonus and Benefits
Our client is an Investment Management company based in Central London. They are embarking on a multi-year transformation which includes the creation of a new data platform and as such have created a new role for a Data Engineer. This is an opportunity to be part of the design and implementation of the data platform as their first dedicated Data Engineer, working alongside selected vendor/service providers. The role will be an important contributor to architecture decisions, working practices, technical design and implementation of new features.
Key Responsibilities:
- Actively participate in the Data Platform implementation project, defining and implementing a fit for-purpose architecture in accordance with business needs.
- Implement necessary data process steps (ingestion, storage/warehousing, curation) for a front-to-back data lifecycle for key data domains.
- Develop pipelines able to support the range of data sources in scope (on-premise SQL/Oracle, SaaS/cloud hosted data sources or vendors via API, file, Snowflake share or proprietary request formats (e.g. Bloomberg DL).
- Collaborate on data TOM and help maintain as it evolves.
- Build an understanding of the existing data flows, enabling involvement in BAU issue resolution.
- Work with multiple departments to align tools and working practices.
- Advise on best practices and new ways of working to enable the business to benefit from the data platform.
- Participate in issue investigations (i.e. SQL ad hoc reports for trade enquiries) and increase understanding of platform data flows and customisations.
Skills and Experience Required:
- Detailed knowledge and hands-on experience of implementing cloud-based distributed and scalable solutions, leveraging modern compute, storage, databases and reporting technologies.
- Experience and understanding of data engineering projects through all stages and states within a financial institution.
- Proven coding skills (Python, Java, SQL), and experience working with large data-sets, both on-prem and cloud-based.
- Strong technical skillset, including expertise in data modelling, experimental design, and execution.
- Understanding of CI/CD pipelines and DevOps practices for data engineering.
- Experience in data integration, ETL/ELT pipeline, and automation/orchestration.
- Experience with Snowflake would be highly beneficial.
- Experience of financial applications and knowledge of investment management practices and asset class financial data preferred.
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