Senior Data Engineer

Artefact
england, ecr eb
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - Databricks

Senior Data Engineer - Snowflake - £110,000 - London - Hybrid

Senior Data Engineer - Snowflake - £100,000

Senior Data Engineer 

Who we are

Artefact is a new generation of data service provider, specialising in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.

Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 1000+ client base around the globe.

We have over 1500 employees across 20 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client.

Job Summary

We are looking for a Senior Data Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment. 

Key Responsibilities

Design, build, and maintain scalable and robust data pipelines using SQL, Python, Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark. Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms. Implement continuous integration and continuous deployment (CI/CD) practices for data pipelines to improve efficiency and quality of data processing. Work closely with data architects, analysts, and other stakeholders to understand business requirements and translate them into technical implementations. Oversee and manage a team of data engineers, providing guidance and mentorship to ensure high-quality project deliverables. Develop and enforce best practices in data governance, security, and compliance within the organisation. Optimise data retrieval and develop dashboards and reports for business teams. Continuously evaluate new technologies and tools to enhance the capabilities of the data engineering function.

Qualifications

Bachelor's or Master’s degree in Computer Science, Engineering, or a related field. 6+ years of industry experience in data engineering with a strong technical proficiency in SQL, Python, and big data technologies. Extensive experience with cloud services such as Azure Data Factory and AWS Glue. Demonstrated experience with Databricks and Snowflake. Solid understanding of CI/CD principles and DevOps practices. Proven leadership skills and experience managing data engineering teams. Strong project management skills and the ability to lead multiple projects simultaneously. Excellent problem-solving skills and the ability to work under tight deadlines. Strong communication and interpersonal skills. Excellent understanding of data architecture including data mesh, data lake and data warehouse.

Preferred Qualifications:

Certifications in Azure, AWS, or similar technologies. Certifications in Databricks, Snowflake or similar technologies Experience in the leading large scale data engineering projects

Working Conditions

This position may require occasional travel. Hybrid work arrangement: two days per week working from the office near St. Paul’s 

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.