Data Engineer: Cloud Pipelines & Analytics

BGBx; Greater London; On-site; GBP 51,000 - 64,000; Full time

Benefits offered by this job

Health insurance

Retirement plans

Paid time off

Holidays

Wellness benefits

Life insurance

Learning & development

Collaborative culture

Job summary

BGBx is seeking a Data Engineer with 3-5 years of experience to design, build, and maintain data pipelines that extract, process, and transform data into reliable datasets for analysis. You will work with Python and SQL, across cloud data warehouses, and orchestration tools to support analysts, data scientists, and product teams.

The role involves large-scale datasets, cloud-based infrastructure, and a fast-moving environment focused on healthcare data solutions.

Qualifications

• 3-5 years hands-on data engineering experience building and maintaining data pipelines.
• Strong Python and SQL skills.
• Experience with at least one cloud data warehouse (BigQuery/Redshift/Snowflake/etc.).
• Familiarity with orchestration tools such as Airflow, Dagster, Prefect, or Flyte.
• Cloud platform experience with GCP, AWS, or Azure.
• Strong database knowledge and problem-solving skills.

Responsibilities

• Design, build, and maintain ETL/ELT data pipelines.
• Extract, clean, transform, and model data from internal and external sources.
• Develop data solutions using Python and SQL.
• Work with large-scale datasets and cloud-based data infrastructure.
• Support data consumers, including analysts, data scientists, and product teams.
• Monitor pipeline health, troubleshoot failures, and optimize performance.

Skills

Data engineering experience (3-5 yrs)

Python

SQL

Tools

BigQuery

Redshift

Snowflake

ClickHouse

Greenplum

Vertica

Airflow

Dagster

Prefect

Flyte

Job description

BGBx is seeking a Data Engineer with 3-5 years of experience to design, build, and maintain data pipelines that extract, process, and transform data into reliable datasets for analysis. You will work with Python and SQL, across cloud data warehouses, and orchestration tools to support analysts, data scientists, and product teams.

The role involves large-scale datasets, cloud-based infrastructure, and a fast-moving environment focused on healthcare data solutions.