Data Engineer – Investment Management

4 weeks ago

London, United Kingdom psd group Full time

Data Engineer – Investment Management / Asset Management

£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 practice 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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