Data Engineer - Actuarial - Asset Management Data - Investment/Insurance

Orbis Group; Swindon; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading fintech firm in the UK seeks a Senior Data Engineer to design and implement end-to-end data solutions. The candidate will work with large-scale financial datasets and automate processes. Applicants must have strong experience in investment, asset management, or actuarial operations, specifically through tools like Python, SQL, and cloud platforms such as GCP and Databricks. Join a dynamic team offering a pivotal role in transforming investment analytics.

Qualifications

• Experience with financial securities and portfolio valuations.
• Hands-on expertise in building analytic pipelines using Python and SQL.
• Knowledge of automation processes and integrating multiple data sources.

Responsibilities

• Build end-to-end data pipelines in Python and SQL.
• Automate processes and deliver actionable insights.
• Integrate various actuarial and asset management datasets.

Skills

Financial securities knowledge

Analytical pipeline development

Cloud data solutions

Actuarial analytics expertise

Tools

Python

SQL

GCP (BigQuery)

DBT

Databricks

Job description

Job Overview

Our client, an award-winning fintech specialising in investment and insurance data solutions, is urgently seeking a Senior Data Engineer. You will work with actuarial and asset management datasets, building end-to-end data pipelines in Python (Pandas, NumPy), SQL, GCP (BigQuery), DBT, and Databricks. This role focuses on large-scale financial data, automating processes, integrating multiple data sources, and delivering actionable insights to senior stakeholders. Only candidates with direct experience in investment, asset management, or reinsurance/insurance operations handling financial securities or actuarial outputs will be considered.

Key Qualifications

• Actuarial / Asset Management Data: Hands‑on experience with financial securities, portfolio valuations, or actuarial outputs in investment, reinsurance, or life insurance environments.
• Python & SQL: Build analytical pipelines and scalable data solutions using Pandas, NumPy, and SQL.
• Cloud / Tools: Experience with GCP (BigQuery), DBT, and Databricks.
• Domain Expertise: Prior delivery of projects in investment operations, reinsurance, or actuarial analytics.