AWS Lead Data Engineer - Real-Time Analytics

Harnham; United Kingdom; Remote; GBP 70,000 - 105,000; Full time

Benefits offered by this job

Remote-friendly across UK/Europe

Clear progression opportunities

Job summary

Harnham is expanding a high-performance data engineering team to support real-time, high-volume analytics for a digital-first consumer platform. You will design, build, and own end-to-end data pipelines, ensuring reliability, scalability, and production-grade quality from day one.

Join a fully remote team across the UK and Europe, collaborating with analytics, product, and engineering to enable faster, data-driven decisions while adopting modern tooling and best practices.

Qualifications

• Strong commercial experience as a data engineer in modern cloud environments.
• Proficient in building real-time and batch data pipelines with reliability.
• Hands-on with data modeling and analytics best practices.

Responsibilities

• Design, build, and own end-to-end data pipelines for real-time and batch analytics.
• Work on high-volume, low-latency data use cases with emphasis on reliability and scalability.
• Develop production-grade data solutions with CI/CD, testing, and version control.
• Contribute to data models and analytics layers used across the business.
• Help mature staging, testing, and deployment processes for the data platform.
• Collaborate with analytics, product, and engineering teams to enable better decision making.

Skills

Python

SQL

PySpark

Data modeling

Git

CI/CD

Cloud experience

Tools

Snowflake

dbt

Iceberg

Dagster

Airflow

AWS

S3

Glue

EKS

Job description

Harnham is expanding a high-performance data engineering team to support real-time, high-volume analytics for a digital-first consumer platform. You will design, build, and own end-to-end data pipelines, ensuring reliability, scalability, and production-grade quality from day one.

Join a fully remote team across the UK and Europe, collaborating with analytics, product, and engineering to enable faster, data-driven decisions while adopting modern tooling and best practices.