初级数据工程师

Join Colibri DigitalBorn in the cloud, Colibri is one of the fastest-growing Cloud Consultancies in the UK. We are Select partners with AWS and our recent attainment of Gold competency with Microsoft proves our excellence in evolving cloud and data technologies.Our culture is built around trust, continuous learning and technical excellence. You'll work alongside experienced consultants who are passionate about developing people and sharing knowledge, giving you the opportunity to accelerate your career from day one.

Please Note:To be considered for this opportunity, you must:

• Have the unrestricted right to work in the UK (we are unable to offer visa sponsorship for this position).

• Be based in the UK and be able to travel to London when required for team collaboration, training and customer engagements.

• Have approximately 6–12 months' practical experience in industry, ideally software engineering through a placement year, internship, graduate programme or similar commercial experience.

• Recent graduates with relevant placement or internship experience are strongly encouraged to apply.

Appreciate if you can apply only if you fit the above criteria.

About the RoleWe're looking for an ambitious Graduate Data Engineer to join our growing Data Engineering Practice.This is an exciting opportunity for someone at the start of their career who is passionate about technology and wants to become a data engineering consultant.During your first 12 months, you'll follow a structured development programme combining formal technical training, mentoring and hands-on engineering experience. You'll develop practical skills across SQL, Python, Git, Databricks, Azure and modern cloud data engineering before progressing into customer-facing consultancy work.Initially, you'll take ownership of internal engineering initiatives including reporting, reusable frameworks, engineering assets and technical documentation. As your capability develops, you'll begin contributing to customer projects alongside our experienced consultants.

This role has been created to strengthen our internal engineering capability whilst providing an accelerated development pathway into consulting.

Key Responsibilities

What You’ll Be Doing

• Develop and maintain internal reporting solutions that support operational and business decision-making.

• Build, maintain and improve reusable engineering frameworks, templates and accelerators.

• Produce high-quality technical documentation, standards and engineering guidance.

• Support the development of internal tooling that improves delivery consistency and engineering quality.

• Learn and apply data engineering best practices through structured mentoring and formal training.

• Work alongside experienced Data Engineers to understand cloud data platforms and modern engineering techniques.

• Participate in code reviews and technical knowledge sharing.

• Shadow customer workshops and consulting engagements.

• Gradually contribute to customer delivery projects as your technical capability develops.

• Continuously build your technical knowledge across Cloud, Data and AI technologies.

What You'll Learn
Our structured development programme will provide hands-on experience across:

• SQL

• Python

• Git

• Databricks

• Azure Data Services

• Data modelling

• ETL & ELT engineering

• CI/CD fundamentals

• Data engineering best practices

• Technical documentation

• Consulting and stakeholder management

• Customer delivery

Skills, Knowledge and Expertise

Requirements

Essential

• Degree (or expected degree) in Computer Science, Data Science, Software Engineering, Mathematics or another relevant STEM subject.

• Approximately 6–12 months' practical experience through a placement year, internship or graduate programme.

• Basic knowledge of SQL.

• Basic knowledge of Python.

• Strong analytical and problem-solving skills.

• Excellent written and verbal communication skills.

• Genuine enthusiasm for Cloud, Data Engineering and AI technologies.

• Strong attention to detail.

• Willingness to learn and continuously develop.

• Ability to work independently and collaboratively.

Desirable

• Exposure to Azure, AWS or Databricks.

• Experience using Git or other version control systems.

• Understanding of relational databases and data modelling.

• Familiarity with ETL/ELT concepts.

• Experience gained through university projects, hackathons or personal development.

• The Ideal Candidate

• We're looking for someone who is:

• Curious and eager to learn.

• Passionate about technology.

• Comfortable asking questions and learning from experienced colleagues.

• Organised with excellent attention to detail.

• A natural problem solver.

• Collaborative and enjoys working within a team.

• Interested in building a long-term career in Data Engineering and Consulting.

Working Pattern
This is a primarily remote role. However, you'll be expected to attend our London office and customer locations when required for collaboration, training, workshops and team events.

Benefits

What You’ll Get

• Competitive salary.

• Structured graduate development programme.

• Dedicated mentoring from experienced consultants.

• Exposure to modern Cloud, Data and AI technologies.

• Opportunity to work alongside recognised technical experts.

• Clear career progression into a customer-facing Data Engineering Consultant role.

• Regular technical training and certification support.

• Flexible remote working with regular team meet-ups and socials.

• A collaborative culture focused on learning, innovation and technical excellence.

Why Join Colibri?
At Colibri Digital, you'll join a consultancy where learning is continuous, collaboration is encouraged and your development is genuinely invested in. You'll work on modern cloud technologies, solve complex customer problems and build a career alongside some of the industry's most experienced Cloud, Data and AI consultants.

If you're looking for more than just a graduate role, and want to kick-start a career in consulting, we'd love to hear from you!

Originally posted on Himalayas