Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Principal Data Engineer (Azure, PySpark, Databricks)

PEXA
Thame
1 week ago
Create job alert
Principal Data Engineer

We are Smoove, part of the PEXA Group, simplifying the home moving and ownership experience. We are seeking an experienced Principal Data Engineer to define, lead, and scale the technical strategy of our data platform. This senior, hands‑on leadership role sits at the intersection of architecture, governance, and engineering excellence, shaping how data is collected, processed, and delivered across the organisation.

Role Responsibilities
  • Design and oversee scalable, performant, and secure architectures on Databricks and distributed systems.
  • Anticipate scaling challenges and ensure platforms are future‑proof.
  • Lead the design and development of robust, high‑performance data pipelines using PySpark and Databricks.
  • Define and ensure testing frameworks for data workflows.
  • Ensure end‑to‑end data quality from raw ingestion to curated, trusted datasets powering analytics.
  • Establish and enforce best practices for data governance, lineage, metadata, and security controls.
  • Ensure compliance with GDPR and other regulatory frameworks.
  • Act as a technical authority and mentor, guiding data engineers.
  • Influence cross‑functional teams to align on data strategy, standards, and practices.
  • Partner with product, engineering, and business leaders to prioritise and deliver high‑impact data initiatives.
  • Build a culture of data trust, ensuring downstream analytics and reporting are always accurate and consistent.
  • Evaluate and recommend emerging technologies where they add value to the ecosystem.
Skills & Experience Required
  • Broad experience as a Data Engineer including technical leadership.
  • Broad cloud experience, ideally both Azure and AWS.
  • Deep expertise in PySpark and distributed data processing at scale.
  • Extensive experience designing and optimising in Databricks.
  • Advanced SQL optimisation and schema design for analytical workloads.
  • Strong understanding of data security, privacy, and GDPR/PII compliance.
  • Experience implementing and leading data governance frameworks.
  • Proven experience leading the design and operation of a complex data platform.
  • Track record of mentoring engineers and raising technical standards.
  • Ability to influence senior stakeholders and align data initiatives with wider business goals.
  • Strategic mindset with a holistic view of data reliability, scalability, and business value.

We welcome all qualified candidates; Smoove is an equal opportunity employer. We provide a safe and inclusive environment that values diversity and fosters innovation.


#J-18808-Ljbffr

Related Jobs

View all jobs

Principal Data Engineer/Architect

Principal Data Engineer/Architect

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.