Hybrid Full-Stack Data Engineer: Pipelines & Apps

Peaple Talent; Harrow; Hybrid; GBP 45,000 - 60,000; Full time

Benefits offered by this job

Hybrid working

Salary £45k-£60k

Pension contributions

Career progression

Job summary

Peaple Talent is seeking a Full Stack Data Engineer for a data-leaning hybrid role. You will own data-intensive applications from pipelines to backend services, working across clients with a focus on data, integration and platforms.

The role suits someone early in their career who wants breadth across data engineering, backend, and UI layers, with variety across projects and clients and strong data/AI stack exposure.

Qualifications

• Strong proficiency in Python and SQL.
• Working knowledge of AWS is advantageous.
• Hands-on data integration with ETL/ELT pipelines.
• Backend development experience including API design.
• Version control with Git.
• Excellent written and spoken English.

Responsibilities

• Build, operate and optimise data pipelines and data platforms in a hybrid cloud environment.
• Design and develop data-intensive applications including back-end services and APIs.
• Develop and maintain databases, data warehouses and data lakes with governance.
• Prepare data for analytics, dashboards and AI solutions.
• Own existing applications including support and continuous improvement.
• Manage deployment pipelines, version control and CI/CD.
• Collaborate with consultants, analysts, project managers and clients to turn business needs into solutions.

Skills

Python

SQL

AWS

Data pipelines

Back-end development

Git

English

Tools

Snowflake

Databricks

dbt

Power BI

React/Next.js

Job description

Peaple Talent is seeking a Full Stack Data Engineer for a data-leaning hybrid role. You will own data-intensive applications from pipelines to backend services, working across clients with a focus on data, integration and platforms.

The role suits someone early in their career who wants breadth across data engineering, backend, and UI layers, with variety across projects and clients and strong data/AI stack exposure.