At a Glance
- Tasks: Design and maintain scalable data pipelines using SQL and Python, leading a team of data engineers.
- Company: Join Artefact, a cutting-edge data service provider transforming businesses with data-driven solutions.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and career development.
- Why this job: Make a real impact in a fast-paced environment while working with the latest data technologies.
- Qualifications: 3+ years in data engineering, strong skills in SQL, Python, and cloud technologies.
The predicted salary is between 63000 - 77000 £ per year.
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.
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 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 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 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 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.3+ years of industry experience in data engineering with a 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 Dev Ops/Dev Sec Ops practices.
Proven leadership skills and experience managing data engineering teams.
Proficient in leveraging AI-assisted workflows to optimise task efficiency.
Excellent understanding of data architecture involving data mesh, data lake, data warehouse and data lakehouse.
Certifications in Azure, AWS, or GCP.
Experience in the leading large scale data engineering projects.
Working Conditions Hybrid work arrangement: two-three days per week working from the office
Senior Engineer, Data Engineering in London employer: Artefact
Artefact is an exceptional employer, offering a vibrant work culture in the heart of London where innovation thrives. With a strong focus on employee growth and development, we provide opportunities to lead cutting-edge projects that integrate AI technologies into SEO practices, ensuring our team members are at the forefront of industry advancements. Join us for a meaningful career where your expertise will drive impactful results for enterprise clients while enjoying the collaborative and dynamic environment we foster.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer, Data Engineering in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Artefact!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Engineer, Data Engineering at Artefact.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Artefact.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Engineer, Data Engineering at Artefact, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Engineer, Data Engineering in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Artefact, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Artefact. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Artefact
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Artefact!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
