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Senior Data Engineer (Python, Databricks) - CER Financial

CER FinancialLondon🇬🇧United KingdomPosted 31 Jul 2026

Why This Role Stands Out

Elevate your data engineering career by designing and optimizing scalable data pipelines with Python and Databricks for a leading international bank, offering a competitive daily rate and hybrid flexibility. You'll thrive in this role if you possess extensive experience in ETL/ELT, data modeling, and cloud platforms, and are eager to mentor others and contribute to impactful analytics and ML initiatives. Apply now to leverage your skills and make a significant impact.

Quick Overview

Salary
£500 - £900/mo
Work Type
Hybrid
Schedule
Full Time
Level
Mid Senior

Job Description

Senior Data Engineer (Python, Databricks)

London

Hybrid (3/2 split)

6-month contract

£500 - £900 per day (via Umbrella)

cer Financial are working alongside an international bank who are looking for an experienced Senior Data Engineer to join their team on an initial 6-month contract. This is a hybrid role, requiring 3 days per week in the office.

Responsibilities:

· Design, build and optimise scalable data pipelines using Python and Databricks.

· Develop ETL/ELT workflows with Spark and Delta Lake.

· Build and maintain Lakehouse data models and architectures.

· Ensure data quality, governance and platform reliability.

· Optimise large-scale data processing and support analytics and ML initiatives.

· Mentor junior engineers and promote engineering best practices.

What the candidate needs:

· 10+ years' experience in Data Engineering.

· Strong Python and Databricks expertise, including Spark/PySpark and Delta Lake.

· Experience building scalable ETL pipelines and working with SQL.

· Knowledge of cloud platforms (AWS, Azure or GCP).

· Experience with modern data warehouses such as Snowflake, Redshift or BigQuery.

· Familiarity with Airflow or Databricks Workflows.

· Databricks certifications and experience with Kafka, Docker, Kubernetes or CI/CD are advantageous.

Skills

Docker
GCP
SQL
AWS
ETL
Snowflake
Airflow
Azure
BigQuery
Databricks
Kafka
Kubernetes
Python
Redshift

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