Senior Data Engineer

Artefact
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - Data Migration

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.

Navigating Data Science Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Data science has taken centre stage in the modern workplace. Organisations rely on data-driven insights to shape everything from product innovation and customer experience to operational efficiency and strategic planning. As a result, there is a growing need for skilled data scientists who can analyse large volumes of data, build predictive models, communicate findings effectively, and collaborate cross-functionally. If you are looking to accelerate your data science career—or even land your first role—attending data science career fairs can be a game-changer. Unlike traditional online applications, face-to-face interactions let you showcase your personality, passion, and communication skills in addition to your technical expertise. However, to stand out in a busy environment, you need a clear strategy: from polishing your personal pitch and asking thoughtful questions to following up with a memorable message. In this article, we’ll guide you through every step of making a strong impression at data science career fairs in the UK and beyond.

Common Pitfalls Data Science Job Seekers Face and How to Avoid Them

Data science has become a linchpin for decision-making and innovation across countless industries, from finance and healthcare to tech and retail. The demand for data scientists in the UK continues to climb, with businesses seeking professionals who can interpret complex datasets, build predictive models, and communicate actionable insights. Despite this high demand, the job market can be extremely competitive—and many applicants unknowingly fall into avoidable traps. Whether you’re an aspiring data scientist fresh out of university, a professional transitioning from a quantitative role, or a seasoned analyst looking to expand your skill set, it’s crucial to navigate your job search effectively. In this article, we explore the most common pitfalls data science job seekers face and provide pragmatic advice to help you stand out. By refining your CV, portfolio, interview strategies, and communication skills, you can significantly increase your chances of landing a rewarding data science role. If you’re looking for your next data science job in the UK, don’t forget to explore the listings at Data Science Jobs. Read on to discover how to avoid critical mistakes and position yourself for success.

Career Paths in Data Science: From Entry-Level Analysis to Leadership and Beyond

Data is the lifeblood of modern business, and Data Scientists are the experts who turn raw information into strategic insights. From building recommendation engines to predicting market trends, the impact of data science extends across virtually every industry—finance, healthcare, retail, manufacturing, and beyond. In the UK, data-driven decision-making is critical to remaining competitive in a global market, making data science one of the most sought-after career paths. But how does one launch a career in data science, and how can professionals progress from entry-level analysts to senior leadership roles? In this comprehensive guide, we’ll explore the typical career trajectory, from junior data scientist to chief data officer, discussing the key skills, qualifications, and strategic moves you need to succeed. Whether you’re a recent graduate, transitioning from another technical field, or an experienced data scientist aiming for management, you’ll find actionable insights on forging a successful career in the UK data science sector.