Job Description
Data Engineer
Department: Services
Employment Type: Permanent
Location: Remote, UK
At Colibri Digital, we're at the forefront of AI, Big Data and Cloud technologies, helping global organisations solve complex data challenges.
This is not an entry-level position. As a Data Engineer, you'll work alongside experienced architects and engineers to deliver modern cloud data platforms, scalable pipelines and analytics solutions for enterprise clients across a variety of industries. Every project is different, giving you the opportunity to continuously expand your technical expertise while working with cutting-edge technologies.
This is a permanent, fully remote opportunity with long-term career progression as you grow within our Data Engineering practice.
Key Responsibilities
As a Data Engineer, you'll play an important role in designing, building and delivering cloud-native data solutions for enterprise clients.
Your responsibilities will include:
- Design, develop and maintain scalable ETL/ELT pipelines using dbt, Snowflake and/or Databricks
- Build and optimise cloud-native data lake solutions using Amazon S3
- Develop production-grade data pipelines using AWS services including Glue, Lambda, Step Functions or MWAA
- Build scalable data models that support analytics and business reporting.
- Optimise SQL transformations and data processing for performance and cost efficiency.
- Develop dashboards and reporting solutions using Databricks Dashboards, Snowsight or Amazon QuickSight
- Collaborate with architects, engineers and client stakeholders to deliver high-quality production solutions.
- Follow software engineering best practices including version control, testing and CI/CD.
Skills, Knowledge and Expertise
We're looking for Data Engineers with 3+ years of commercial experience delivering production data engineering solutions. You'll work with experienced architects and engineers to design, build and optimize modern cloud data platforms for enterprise clients.
Essential Skills & Experience
Strong hands-on experience with dbt is essential. This is a key requirement for the role, with proven experience developing data transformation models and implementing data modelling best practices using dbt.
- 3+ years' commercial experience as a Data Engineer delivering production data solutions.
- Strong SQL skills.
- Strong Python programming experience.
- Commercial experience using Snowflake or Databricks as enterprise data platforms.
- Strong hands-on experience with dbt for data transformation and modelling.
- Experience building and maintaining modern ETL/ELT pipelines.
- Experience working within AWS cloud environments
- Experience building cloud-native data lake solutions using Amazon S3
- Experience using AWS-native orchestration and ingestion services such as AWS Glue, AWS Lambda, AWS Step Functions, or MWAA (Apache Airflow)
- Experience designing and optimising data pipelines for performance, scalability and reliability.
- Experience developing dashboards or reporting solutions using Databricks Dashboards, Snowsight or Amazon QuickSight
- Good understanding of data modelling principles.
- Familiarity with Git and CI/CD practices.
- Excellent communication skills with the ability to work collaboratively within technical teams and with client stakeholders.
Desirable
- Databricks certifications.
- Snowflake certifications.
- Experience working in consulting or client-facing environments.
- Infrastructure as Code (Terraform or CloudFormation).
- Knowledge of data governance and security best practices.
- Experience working within Agile delivery teams.
Please note: This role requires prior commercial experience delivering production data engineering solutions and is not suitable for graduates or candidates seeking their first Data Engineering position.
- Have proven experience building data transformation models, implementing data modelling best practices and developing production-ready ELT pipelines using dbt.
- Have experience delivering production data engineering projects rather than only academic or personal projects.
- Can work independently while collaborating effectively within delivery teams.
- Enjoy solving complex technical challenges.
- Take ownership of their work from design through deployment.
- Are passionate about continuous learning and developing new technical skills.
Benefits
- Fully remote working.
- Work on exciting enterprise-scale projects across multiple industries.
- Modern Azure and Databricks technology stack.
- Access to AWS, Microsoft and Databricks certifications.
- Work alongside highly experienced architects and engineers.
- Clear career progression into Senior Data Engineer and beyond.
- Collaborative engineering culture focused on technical excellence.
- Competitive salary and benefits.
