How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior Data Engineer
Senior Data Engineer
Who We Are
Artefact is a new-generation 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 are enjoying skyrocketing growth.
Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet 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 globally.
We have over 2000 employees across 26 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets—state-of-the-art data technologies, lean AI and 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.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Responsibilities
- Design, build, and maintain scalable and robust data pipelines using SQL and Python, and leveraging any of the following: 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 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
Core Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 3+ years of industry experience in data engineering with strong technical proficiency in SQL, Python, and big data technologies.
- Expertise in building scalable data workflows using cloud-native orchestration tools and distributed data processing frameworks.
- Demonstrated experience with Infrastructure as Code tooling such as Terraform.
- Solid understanding of CI/CD principles and DevOps/DevSecOps practices.
- Proven leadership skills and experience managing data engineering teams.
- Excellent problem-solving skills, adaptability, and ability to work with ambiguity.
- Proficiency in leveraging AI-assisted workflows to optimise task efficiency.
- Strong communication and interpersonal skills.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
- Excellent understanding of data architecture involving data mesh, data lake, data warehouse, and data lakehouse.
Preferred Qualifications
- Certifications in Azure, AWS, or GCP.
- Certifications in Databricks, Snowflake, or similar technologies.
- Experience in leading large-scale data engineering projects.
Working Conditions
- Hybrid work arrangement: Two to three days per week working from the office.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location