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TyneStack Ltd

Data Engineer

Newcastle upon Tyne
Posted about 21 hours ago
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Data Engineer (Python / SQL / Microsoft Fabric)

Location: Newcastle upon Tyne | 3 Days onsite
Type: Full-time, Permanent

Overview

A large Newcastle based organisation is looking to appoint a hands-on Data Engineer to join its established and growing Data team.

This role is particularly focused on strong commercial Python and SQL experience. You'll be responsible for building and maintaining data pipelines, ingesting and transforming data from multiple systems and developing reliable datasets that support Analytics, Data Science and wider business teams.

The environment is continuing to evolve towards modern cloud Data Engineering technologies, including Microsoft Fabric and Python notebooks. You don't need to already be an expert across every part of the Microsoft data stack, but you should have strong Data Engineering fundamentals and be confident using Python and SQL within real commercial environments.

Key Responsibilities

  • Build, maintain and optimise data pipelines and ingestion processes
  • Use Python to transform, process and manipulate data
  • Write complex, efficient SQL queries and procedures
  • Develop solutions increasingly using Python notebooks
  • Build ETL and ELT processes across multiple data sources
  • Support data warehouse and dimensional modelling solutions
  • Transform transactional data into structures suitable for analytics and reporting
  • Work with Microsoft Fabric and wider Azure data technologies
  • Monitor pipelines and resolve data quality, reliability and performance issues
  • Collaborate with Analytics, Data Science and business teams to deliver practical engineering solutions

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Requirements

  • Strong commercial Python experience within Data Engineering
  • Strong commercial SQL experience, including complex queries and data transformations
  • Experience building and maintaining data pipelines
  • Commercial experience with ETL and/or ELT development
  • Experience ingesting and transforming data from multiple source systems
  • Understanding of data warehousing and dimensional modelling
  • Good understanding of data quality, validation and reliable data processing
  • Strong problem-solving skills and a genuine Data Engineering mindset

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Desirable

  • Microsoft Fabric experience
  • PySpark, Spark or Databricks exposure
  • Azure Data Factory or Azure Data Lake experience
  • Experience with Python notebooks
  • Understanding of OLTP and OLAP architectures

What’s on Offer

  • Hybrid working after probation
  • Exposure to Microsoft Fabric and modern Azure data technologies
  • Opportunity to develop further with Python notebooks and cloud Data Engineering
  • Genuine progression opportunities within an established Data team
  • Collaborative environment working alongside Analytics and Data Science professionals

Apply

If you're a Data Engineer with strong commercial Python and SQL skills and want to continue developing within a modern Microsoft data environment, apply now or get in touch for a confidential discussion.

We're particularly interested in people who see themselves as Data Engineers rather than primarily Data Analysts or BI professionals.

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Skills

Python
SQL
Microsoft Fabric
ETL
ELT
Data Pipelines
Dimensional Modelling
Data Warehousing
Azure Data Factory
Azure Data Lake
PySpark
Spark
Databricks
Python Notebooks
OLTP
OLAP

Location

Newcastle upon Tyne, England, United Kingdom

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