Principal Data Engineer

Principal Data Engineer

Leeds Full-Time 48000 - 64000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead hands-on development and mentor the engineering team in data governance.
  • Company: Join a forward-thinking financial services company modernising their data platform.
  • Benefits: Enjoy a competitive salary up to £80,000 plus fantastic extra benefits.
  • Why this job: Make a real impact on data engineering while working with advanced tech and a supportive team.
  • Qualifications: Strong Azure experience, Databricks proficiency, and Terraform skills required.
  • Other info: This is a hybrid role based in Leeds, perfect for tech enthusiasts.

The predicted salary is between 48000 - 64000 £ per year.

Overview

PRINCIPAL DATA ENGINEER

£80,000 + BENEFITS

LEEDS (Hybrid)

Looking for a role where you can truly influence how data engineering is done-while still getting stuck into the tech yourself?

The Company

I\’m working with a central data function in the financial services industry that\’s undergoing a full modernisation of their data platform. They\’ve got technically advanced teams across the wider business and are now building out a core engineering team to unify, elevate and support that community.

The Role

It\’s a strategic, hands-on role where you\’ll work closely with DevOps, Product, and business partners to unlock the value of data through modern, secure and governed pipelines.

  • Lead hands-on development work using Azure, Databricks, and Terraform (IaC)
  • Support the migration from legacy platforms to a more modern cloud stack
  • Act as a mentor and technical guide to the wider engineering team
  • Implement data governance requirements
  • Collaborate with non-technical stakeholders to ensure delivery aligns to business needs
  • Stay close to the ML lifecycle

Your Skills and Experience

YOUR SKILLS AND EXPERIENCE:

A successful Principal Data Engineer will have the following skills and experience:

  • Strong hands-on experience with Azure
  • Proficient in Databricks
  • Skilled in Terraform and Infrastructure as Code practices
  • Exposure to contai…

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Principal Data Engineer employer: Harnham - Data & Analytics Recruitment

Join a forward-thinking financial services company in Leeds, where innovation meets collaboration. As a Principal Data Engineer, you'll not only influence the future of data engineering but also enjoy a supportive work culture that prioritises employee growth and development. With a hybrid working model and access to cutting-edge technology, this role offers a unique opportunity to make a significant impact while enjoying a competitive salary and excellent benefits.
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Contact Detail:

Harnham - Data & Analytics Recruitment Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Principal Data Engineer

✨Tip Number 1

Familiarise yourself with the latest trends in data engineering, especially around Azure and Databricks. This will not only help you during interviews but also show your genuine interest in the role.

✨Tip Number 2

Network with current employees or professionals in the financial services sector. Engaging with them can provide insights into the company culture and expectations, which can be invaluable during your application process.

✨Tip Number 3

Prepare to discuss your hands-on experience with Terraform and Infrastructure as Code. Be ready to share specific examples of how you've implemented these technologies in past projects.

✨Tip Number 4

Brush up on your mentoring skills. Since the role involves guiding other engineers, think of ways you can demonstrate your leadership and collaboration abilities in previous roles.

We think you need these skills to ace Principal Data Engineer

Azure
Databricks
Terraform
Infrastructure as Code (IaC)
Containers
Kubernetes
Data Governance
Machine Learning Operations (ML Ops)
Collaboration Skills
Mentoring and Coaching
Problem-Solving Skills
Cloud Migration
DevOps Practices
Technical Documentation

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your hands-on experience with Azure, Databricks, and Terraform. Use specific examples from your past roles that demonstrate your technical skills and how you've influenced data engineering practices.

Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your experience aligns with their needs, particularly in modernising data platforms and collaborating with cross-functional teams.

Showcase Leadership Skills: Since the role involves mentoring and guiding the engineering team, include examples of your leadership experience. Highlight any instances where you’ve successfully led projects or supported team members in their development.

Highlight Collaboration Experience: Emphasise your ability to work with non-technical stakeholders. Provide examples of how you've ensured that technical solutions align with business needs, showcasing your communication skills and understanding of the ML lifecycle.

How to prepare for a job interview at Harnham - Data & Analytics Recruitment

✨Showcase Your Technical Skills

Be prepared to discuss your hands-on experience with Azure, Databricks, and Terraform. Bring examples of past projects where you've successfully implemented these technologies, as this will demonstrate your capability to handle the technical demands of the role.

✨Understand the Business Context

Since the role involves collaborating with non-technical stakeholders, make sure you can articulate how data engineering aligns with business objectives. Research the company’s goals and think about how your work can support their strategic vision.

✨Emphasise Mentorship Experience

As a Principal Data Engineer, you'll be expected to mentor others. Prepare to share instances where you've guided junior engineers or contributed to team development, highlighting your leadership skills and ability to foster a collaborative environment.

✨Familiarise Yourself with ML Ops Concepts

Since the role requires staying close to the ML lifecycle, brush up on ML Ops concepts. Be ready to discuss how you can integrate data engineering practices with machine learning workflows, showcasing your understanding of the broader data ecosystem.

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