Python Data Engineer: Build Scalable ETL Pipelines

REPLY; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Private Healthcare Insurance

25 Days Annual Leave + Bank Holidays

Flexible Working

Cycle to Work and Electric Vehicle

Gym Membership Benefits

EAP with Help@Hand

Job summary

Solirius Reply, part of the Reply Group, seeks a Python Developer with strong data engineering experience to join our high-performing engineering team in the UK. You will design and maintain data-heavy Python applications and robust ETL/ELT pipelines within secure environments.

You will engage with cross-functional teams to deliver scalable data solutions, ensure data quality and governance, and contribute to the evolution of our data platforms with modern engineering practices.

Qualifications

• Proven experience developing Python applications and services.
• Design and build scalable ETL/ELT pipelines for structured and unstructured data.
• Strong SQL skills and relational database experience.

Responsibilities

• Design, develop and maintain Python applications and data processing services.
• Build and optimise ETL/ELT pipelines for data ingestion and delivery.
• Collaborate with data engineers and software engineers to deliver end-to-end data solutions.
• Ensure data quality, governance and security across pipelines.
• Produce clear technical documentation and contribute to architectural decisions.

Skills

Python development

Data engineering

ETL/ELT pipelines

SQL

Git CI/CD

Linux

Security clearance

Education

Bachelor's degree in Computer Science or equivalent

Tools

PySpark

Spark

Pandas

SQL databases

Job description

Solirius Reply, part of the Reply Group, seeks a Python Developer with strong data engineering experience to join our high-performing engineering team in the UK. You will design and maintain data-heavy Python applications and robust ETL/ELT pipelines within secure environments.

You will engage with cross-functional teams to deliver scalable data solutions, ensure data quality and governance, and contribute to the evolution of our data platforms with modern engineering practices.