Investment Platform Data Engineer
Summary
A 4-month inside-IR35 contract for a data engineer at a leading investment management firm in London (2 days per week onsite), enhancing and maintaining investment data platforms and market data integrations. Core stack: Snowflake, Airflow, DBT and Bloomberg, paying up to £800 per day.
To be considered for an interview, please make sure your application is full in line with the job specs as found below.
Investment Platform Data Engineer
- Duration: Initial 4 Months
- Rate: Up to £800 per day - Inside IR35
- Location: London - 2 Days Per Week Onsite
A leading Investment Management organisation is seeking an experienced Investment Platform Data Engineer to join their team on an initial 4-month contract.
Working closely with Investment Technology and Risk teams, you'll play a key role in enhancing and maintaining critical data platforms, supporting market data integrations, and delivering improvements across the investment data landscape.
This is a hands-on role requiring strong data engineering expertise, experience working with financial data, and the ability to operate within a fast-paced investment environment.
Key Skills
- Snowflake
- Airflow
- DBT
- Bloomberg Integrations
Responsibilities
- Design, build and maintain scalable data pipelines and workflows.
- Develop and enhance data solutions using Snowflake, Airflow and DBT.
- Support Bloomberg and market data integrations across investment platforms.
- Ensure the quality, integrity and availability of investment data.
- Troubleshoot and resolve data issues across multiple systems and sources.
- Collaborate with Technology, Data and Investment teams to deliver platform enhancements.
- Support data transformation, reconciliation and validation processes.
- Drive best practices across data engineering, automation and platform support.
Required Experience
- Experience within Investment Management, Asset Management or Financial Services
- Expertise with Snowflake, Airflow and DBT.
- Experience integrating Bloomberg data and services into enterprise platforms.
- Strong SQL and data modelling skills.
- Experience working with large-scale financial or investment datasets. xwwtmva
- Understanding of data quality, governance and monitoring practices.
- Ability to work effectively with both technical and business stakeholders
Reasonable Adjustments:
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