Lead Data Engineer

Lead Data Engineer - Investment Management / Asset Management - Snowflake, Blackrock Aladdin

Our client is a mid sized Investment Management company based in London and is looking for an experienced Data Engineer to join their Development team. The ideal candidate will have experience of working in Investment Management / Asset Management and familiarity with platforms such as Blackrock Aladdin along with the required data engineering and platform skills (although candidates from other financial background such as Investment Banking will be considered).

The role will be instrumental in enabling the team to evolve and maintain the data platform to provide well-governed, curated data to all users, and allow for easier future changes to underlying systems, without compromising the availability of consistent quality data. It will empower business users to make use of data with a range of tools such as BI tools, Python, Alteryx, AI or other data analysis and reporting tools.

Experience Required:

• Strong Snowflake and DBT
• 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, preferably in an Investment Management / Asset Management organisations.
• Proven coding skills (Python, Java, SQL), and experience working with large data-sets, both on-prem and cloud-based.
• Experience of Blackrock Aladdin or similar buy-side platforms would be highly advantageous.
• Strong technical skillset, including expertise in data modelling, experimental design, and execution.
• Understanding of CI/CD pipelines and DevOps practices for data engineering.
• Understanding of data governance and data security practices.
• Experience in data integration, ETL/ELT pipeline, and automation/orchestration.
• Knowledge of cloud-based databases and associated development tools, including virtualisation and container technologies, and awareness of cost optimisation associated with their use.
• Experience in data analysis and working knowledge of common project management practices (Agile, Waterfall).

Tech Stack:

• Cloud based data platforms (SnowFlake, Azure).
• Database technologies such as Microsoft SQL Server and Oracle.
• Engineering scripting – OpenFlow, DBT, Airflow and others.
• Message Queues, JSON and associated communications.
• Microsoft M365 platform, with a focus on Teams and DevOps.
• Python, StreamLit, Jupyter Notebooks.