Data Engineer: Cloud Pipelines & Self‑Service Platform

General Atlantic; England; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Medical insurance

Retirement savings

Bonuses and long-term incentives

Job summary

General Atlantic seeks an Associate-level Data Engineer to join the Data Strategy team. You will design, build, and maintain cloud-based data pipelines and self-service data platforms, collaborating with senior engineers, product managers, and infrastructure teams.

The role emphasizes ETL/ELT workflows, data integration from diverse sources, and enabling analytics with Databricks and Azure. A 2–4 year data engineering background and a relevant CS/Eng degree are expected.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
• 2–4 years of experience in data engineering or analytics engineering.
• Exposure to financial services or enterprise data environments is a plus.

Responsibilities

• Design, develop, and maintain cloud-based data pipelines and integration frameworks.
• Build ETL/ELT workflows using Python and SQL; work with Spark and Databricks.
• Develop centralized data services and APIs for analytics, reporting, and applications.
• Create and maintain data models, Curation of datasets for data lakes, hubs, and warehouses.
• Collaborate with cross-functional teams and ensure data quality and reliability.

Skills

Python

SQL

Data pipelines

Cloud platforms

Databricks

Azure

Power BI

Communication

Education

Bachelor’s degree in Computer Science

Tools

Databricks

Snowflake

Azure

Power BI

Job description

General Atlantic seeks an Associate-level Data Engineer to join the Data Strategy team. You will design, build, and maintain cloud-based data pipelines and self-service data platforms, collaborating with senior engineers, product managers, and infrastructure teams.

The role emphasizes ETL/ELT workflows, data integration from diverse sources, and enabling analytics with Databricks and Azure. A 2–4 year data engineering background and a relevant CS/Eng degree are expected.