Data Streaming Engineer

TrueNorth

Greater London, UK

2 days ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.collegerecruiter.com

Tech stack

Java (Programming Language) Airflow Amazon Web Services Data Analysis Microsoft Azure Batch Processing Data Governance Extract Transform Load (ETL) Data Warehousing Distributed Systems Python (Programming Language) Cloud Services

+7 more

Data Streaming Apache Spark Apache Flink Real Time Data Apache Kafka Data Pipelines Databricks

Job description

Contract or Perm

E-commerce

Principal/Staff Data Streaming Engineer

Duration: 6 months or perm
Start Date: ASAP

I’m currently hiring for a cutting-edge e-commerce company based in London that’s making a shift towards a streaming-first data architecture. As part of this transformation, they’re looking for an experienced Staff/Principal Data Streaming Engineer to join on a 6-month contract (outside IR35). The company is also considering permanent applicants for this position. This role is fully remote.

We are unable to offer sponsorship for this position. All candidates must have full right to work in the UK.

The Opportunity

You’ll play a key role in shaping and delivering the technical strategy behind a modern, cloud-native, real-time data platform.

What We’re Looking For

The ideal candidate will bring a strong blend of strategic thinking and hands-on engineering. Specifically, you’ll have:

Proven experience as a Senior Data Engineer, focused on real-time, distributed systems
Deep expertise with modern streaming tools: Flink, Kafka, Spark, Databricks
Strong cloud-native data architecture experience (AWS, GCP, or Azure)
Solid understanding of streaming vs. batch processing paradigms
Experience defining technical strategy and creating actionable roadmaps
Familiarity with broader data ecosystem tools like Airflow, Dagster, DBT
Strong in Python, Scala, or Java
A background in ETL/ELT pipelines, data warehousing, and analytics engineering best practices
Experience working with privacy-sensitive data and implementing data governance frameworks
Clear, confident communication and a collaborative mindset to align diverse stakeholders

Requirements

The ideal candidate will bring a strong blend of strategic thinking and hands-on engineering. Specifically, you’ll have:

Proven experience as a Senior Data Engineer, focused on real-time, distributed systems
Deep expertise with modern streaming tools: Flink, Kafka, Spark, Databricks
Strong cloud-native data architecture experience (AWS, GCP, or Azure)
Solid understanding of streaming vs. batch processing paradigms
Experience defining technical strategy and creating actionable roadmaps
Familiarity with broader data ecosystem tools like Airflow, Dagster, DBT
Strong in Python, Scala, or Java
A background in ETL/ELT pipelines, data warehousing, and analytics engineering best practices
Experience working with privacy-sensitive data and implementing data governance frameworks
Clear, confident communication and a collaborative mindset to align diverse stakeholders