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- Tasks: Develop and maintain data transformation systems using cutting-edge technology.
- Company: Join a dynamic team focused on innovative data solutions across various industries.
- Benefits: Enjoy discounts on restaurants, cinema tickets, and tech products.
- Why this job: Make a real impact by solving complex data challenges in a fun, collaborative environment.
- Qualifications: Experience in data engineering, Python, SQL, and ETL tools like Airflow.
- Other info: Flexible working options available, with excellent opportunities for growth and learning.
The predicted salary is between 36000 - 60000 £ per year.
The Data Engineer plays an important role in the development of our software solution, used by our clients to help them with their complex data transformation challenges. Our system combines the latest ML based techniques with logic-based transformation, overseen by domain experts, to provide innovative solutions to our clients. This role supports the development of the data system focusing on orchestration, resilience and scaling. Additionally, we aim to provide a framework on which our data transformation modules can be developed by a growing team of junior engineers and technical SMEs. The role may also support the implementation of the systems, including deployment and integration with clients’ own data stores, processes and workflows.
Data Hub is a dynamic team of scientists and developers who love solving complex problems. We provide leading edge technology solutions and services to solve our clients’ data transformation and analytics challenges across a range of industries including geothermal, environmental, hydrocarbon and mineral exploration. You will be working in an open and collaborative environment with opportunities to learn, grow, and develop. We have an informal team culture and believe work should be fun and rewarding. You will be based in one of our hub locations (North Wales or Crawley), hybrid or remote will be considered, and you will be working alongside our teams of data engineers, machine learning engineers, software engineers and subject matter experts.
Key Responsibilities
- Contribute to the development of our data platform infrastructure. This includes our orchestration systems, data processing logic and the interactions between system components.
- Help develop a flexible framework for data transformations by creating a modular system where new transformation logic can be easily developed and integrated into our product offering.
- Build robust data pipelines with a focus on dynamic, end-to-end, metadata driven solutions that consider a wide range of implications, such as downstream application/UI data access patterns, maintainability, monitoring, access control etc.
- Influence our choice of architecture and technology. You will be expected to communicate design ideas and solutions clearly through architectural diagrams and documentation to both technical and non-technical stakeholders.
- Awareness of best practices in software and data engineering, writing secure, performant, and maintainable code (Python, SQL). You will have a keen eye for minimising technical debt and optimising performance where it matters.
- Partner with data analysts, data scientists, and other end-users to understand their requirements and ensure the platform and its data are accessible, reliable, and meet project delivery needs.
- Share your work and best practices; collaborate with others; ensure what we build and how we build it aligns to our ambition for growth.
Qualifications and Experience
- Previous experience of designing, building and maintaining data transformations in a system or product setting.
- Ability to write secure and performant code in Python and SQL.
- Significant experience using orchestrators and ETL tools, especially Airflow.
- Significant RDBMS experience (PostgreSQL, Oracle). Experience with other database types such as NoSQL database (e.g. Neo4j, Elastic) or Vector also beneficial.
- Data architecture experience relating to data modelling, data warehousing and schema design (3NF, dimensional modelling, medallion architecture).
- Experience using docker, VCS (git, Gitlab) and knowledge of CI/CD.
- Knowledge of DevOps and DataOps best practices.
- Kubernetes deployment experience.
- Previous experience building web applications together with wide-ranging knowledge of web frameworks, HTTP, networking, security etc.
Benefits Package
- Discounts on nationwide restaurants, cinema tickets and days out through our benefits platform.
- Tech, Travel and Fashion discounts all available through our benefits platform.
Data Engineer in Crawley employer: Viridiengroup
Contact Detail:
Viridiengroup Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Crawley
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Python, SQL, or any cool data transformations you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with orchestration systems and data pipelines, and don’t forget to highlight your collaborative spirit!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our awesome team at StudySmarter.
We think you need these skills to ace Data Engineer in Crawley
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data transformations, orchestration systems, and any relevant technologies like Python and SQL. We want to see how your skills align with what we do!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our dynamic team. Don’t forget to mention any specific projects or experiences that relate to our work at StudySmarter.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex data challenges in the past. We love seeing how you approach problems and come up with innovative solutions, so let us know about your thought process!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining our awesome team at StudySmarter!
How to prepare for a job interview at Viridiengroup
✨Know Your Tech Stack
Make sure you’re familiar with the technologies mentioned in the job description, especially Python, SQL, and any orchestration tools like Airflow. Brush up on your knowledge of RDBMS and NoSQL databases, as well as data architecture principles. Being able to discuss these confidently will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare examples from your past experience where you tackled complex data transformation challenges. Think about how you approached the problem, the solutions you implemented, and the impact it had. This will demonstrate your ability to contribute to the team’s dynamic problem-solving culture.
✨Communicate Clearly
Since you’ll be working with both technical and non-technical stakeholders, practice explaining your ideas and solutions in a clear and concise manner. Use architectural diagrams if possible to illustrate your points. This will highlight your communication skills and your ability to collaborate effectively.
✨Emphasise Team Collaboration
The role involves working closely with data analysts, scientists, and other engineers. Be prepared to discuss how you’ve successfully collaborated in the past, shared best practices, and contributed to a positive team environment. This aligns with the informal and collaborative culture they value.
