Data Engineer

Square One Resources Limited
Glasgow, UK
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
£93,600.0
Working hours
Regular working hours

Tech stack

Java (Programming Language) Agile Methodology Amazon Web Services Profiling Data Warehousing Distributed Systems Memory Management Python (Programming Language) Performance Tuning Standard Sql Concurrency Gitlab
+7 more
Git Data Lakes Pyspark Information Technology Bitbucket Software Version Control Data Pipelines

Job description

Overview

Job Title: Data Engineer

Location: Glasgow/hybrid

Duration: 31/12/2025

Daily rate: £360 per day INSIDE IR35

Role Description

To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.

Accountabilities

  • Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
  • Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.

Skillset Required

  • Experience in Python, PySpark and SQL
  • Experience with AWS is a plus
  • Strong proficiency in Core Java, including Collections, Concurrency, and Memory Management.
  • Proficient in version control systems such as Git, GitLab, or Bitbucket.
  • Strong background in performance tuning, profiling, and resolving production issues in distributed systems.
  • Working knowledge of Agile methodologies and collaborative development practices.

Seniority level

  • Mid-Senior level

Employment type

  • Contract

Job function

  • Information Technology

Industries

  • Information Services and Financial Services

Requirements

  • Experience in Python, PySpark and SQL
  • Experience with AWS is a plus
  • Strong proficiency in Core Java, including Collections, Concurrency, and Memory Management.
  • Proficient in version control systems such as Git, GitLab, or Bitbucket.
  • Strong background in performance tuning, profiling, and resolving production issues in distributed systems.
  • Working knowledge of Agile methodologies and collaborative development practices.

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Good distractions

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

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Core technical practices for robust data engineering

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Utilizing specific tooling for continuous integration and modeling

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Balancing data science skillings alongside systems engineering rigor

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