Data Engineer - Python, Databricks, Snowflake, Azure, Data Engineering, Data Architecture, Data Anal

Data Engineer – Python, Databricks, Snowflake, Azure, Data Engineering, Data Architecture, Data Analytics, Process Automation, Actuarial, Risk, Investment Data – 12-month Fixed Term Contract

A Data Engineer with strong skills in Python and the Databricks ecosystem is sought after by a leading pensions and life insurance specialist to help drive the build of a new centralised investment data platform.

The business is currently reliant on very manual data collection processes and are embarking on a major project to implement a new platform which will automate data ingestion, cleaning/quality control and distribution across their various business units: Risk, Actuarial, Investment.

The key part of this role will involve working with senior stakeholders and wider data engineering tams to define and build the structure that will be used to report on asset data, feeding directly into their investment portfolio.

You will be responsible for designing and building the data architecture, automating processes, defining what reports and outputs look like, and working with the various teams to finetune/optimise data analysis and reporting capabilities within this new platform.

To be successful, you will demonstrate:

• 4 – 6 years in data engineering, with strong Python coding skills
• An in-depth understanding of the Databricks ecosystem and building mature automated data-centric services (Snowflake experience will also be considered)
• A clear and confident communicator with the ability to engage and influence both senior stakeholders and other technical colleagues
• Ability to take the initiative, suggesting alternative/better solutions and pro-actively seeking out additional tasks
• Ideally a background within Financial Services – Banking, Investment Management, Insurance

Please note, this is being offered on a Fixed Term Contract (FTC) basis for a period of 12 months (potential to extend), and visa sponsorship is not on offer.