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

Apply Now

Senior Data Engineer

Hays
Abingdon
3 days ago
Create job alert

Your New Role

We're seeking a Senior Data Engineer to help shape and maintain a modern enterprise data platform. In this role, you'll design and optimise scalable data pipelines and models that bring data from core business systems into Snowflake, enabling analytics, reporting, and data-driven insights across the organisation.You'll translate strategic data architecture into robust technical solutions, ensuring the platform is reliable, performant, and well-structured. You'll champion engineering best practices and contribute to standards that improve data quality, consistency, and usability.Your work will ensure the business has access to trusted, timely, and well-modelled data to support decision-making, operational reporting, and future AI/ML capabilities.

Key Responsibilities
Data Engineering Delivery: Build and maintain high-quality data pipelines and models in Snowflake to support analytics and reporting needs.
Architecture Implementation: Apply defined data architecture standards to ingestion, transformation, storage, and optimisation processes.
Pipeline Development: Develop robust ELT/ETL workflows using dbt and orchestration tools, ensuring reliability and maintainability.
Performance & Cost Optimisation: Configure Snowflake warehouses and implement query optimisation techniques for efficiency.
Data Quality & Governance: Apply data quality checks, lineage tracking, and security standards aligned with InfoSec and regulatory requirements.
Feature Adoption: Leverage Snowflake capabilities (Tasks, Streams, Snowpark, Time Travel, Secure Data Sharing) to improve automation and accessibility.
Collaboration: Work closely with analysts and stakeholders to deliver data products and troubleshoot issues.
Analytics Enablement: Implement dimensional models to provide clean, reusable datasets for reporting and advanced analytics.
Monitoring & Reliability: Maintain monitoring, alerting, and cost-management processes for Snowflake and pipelines.
Continuous Improvement: Contribute to shared engineering standards and best practices across the team.

What You'll Need to Succeed
Proven experience delivering cloud-based data engineering solutions, ideally with Snowflake.
Strong proficiency in SQL, Python, and dbt for transformations and pipeline automation.
Practical experience with Snowflake features and RBAC management.
Familiarity with ingestion tools (Airbyte, Fivetran, Hevo) and cloud services (AWS preferred).
Solid understanding of data modelling, governance principles, and BI enablement (Power BI).
Knowledge of CI/CD and version-controlled development practices in git.
Desirable: Experience with enterprise systems (CRM, BSS/OSS), data migration projects, and supporting platform adoption.
Exposure to Infrastructure as Code tools such as Terraform is advantageous.

What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.
Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at hays.co.uk

TPBN1_UKTJ

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior 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.