Data Engineer

TRIA
Bristol, UK
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
£55,000.0 - £70,000.0
Working hours
Regular working hours

Tech stack

Airflow Microsoft Azure Software as a Service Data Warehousing Apache Spark Kubernetes Data Pipelines

Job description

We’re excited to be recruiting exclusively for a Data Engineer to join an industry leading SaaS group within a global data driven organisation. So, think fast moving, big budget, heaps of autonomy, and a breakaway type culture that is committed to pushing technical boundaries. But, all without the red tape and sluggish pace

The Headlines

A hands-on Engineering role focused on building scalable, high-quality Data Pipelines, where you’ll be given real ownership, exposure to experienced director level mentors & Senior Data Engineers, alongside the opportunity to grow towards senior-level responsibilities.

Tech Stack

Spark Airflow Kubernetes Azure CubeJS

What You’ll Be Doing

  • Data Pipeline Development - designing & developing efficient, scalable & robust Data Pipelines
  • Support and main the data platform to ensure security, reliability, and scalability.
  • Working with the wider engineering team to gather pipeline requirements, project goals & deliver insights where applicable.
  • Collaborating with engineers, product teams, and customer-facing stakeholders

Requirements

  • 3-7 years’ commercial Data Engineering experience
  • Excellent understanding of data modelling principles and data warehousing concepts.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

2:34 min

Capabilities of the Apache Spark processing engine

Ayon Roy · LIVE

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter · World Congress 2022

2:04 min

Comparing offline data analytics with online stream processing

Artem Volk Artem Volk +1 · World Congress 2024

4:04 min

Overview of Kubernetes operators and custom resource definitions

Philipp Krenn · World Congress 2022

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