Our client, a leading financial services organisation undergoing significant growth, is seeking a

Senior Data Engineer

with strong

Databricks

expertise to drive high-value data initiatives within the reinsurance and investment domain. This role centres on building scalable data solutions, optimising analytical workflows, and partnering with senior business experts to deliver insight-driven outcomes.

Key Responsibilities

Develop and optimise data pipelines on Databricks , leveraging Spark for large-scale processing.

Design and implement data models, mapping, and transformation workflows

across complex financial datasets.

Use Python (Pandas, NumPy) and SQL

to support advanced analytics and data manipulation.

Collaborate with business SMEs

to translate requirements into robust, production-ready data solutions.

Integrate Databricks with GCP/BigQuery

to support cloud-native data engineering initiatives.

Essential Skills

Hands-on Databricks experience , including Spark, Delta Lake, and workflow orchestration.

Strong SQL

for complex querying and optimisation.

Python proficiency , especially for data wrangling and automation.

Financial domain knowledge , ideally asset management, investment operations, or asset data.

Degree in investments, accounting, or actuarial science

from a UK university.

Desirable

Experience with

dbt

for transformation pipelines.

Background in

reinsurance, life insurance, or investment-focused projects .

Familiarity with

GCP/BigQuery

in a production environment.

If you're a Databricks-savvy engineer ready to make an immediate impact in a high-performing financial environment,

send your CV

to be considered.

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