Hiring.Camp

Data Engineer

Nasstar

·

Today

Location
Remote, UK
Workplace
Remote
Department
Engineering
Source
Pinpoint

Description

Data Engineer

Department: Services

Employment Type: Permanent

Location: Remote, UK



Description

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.

Skills

PythonAWSAzureTerraformCI/CDSQLAirflowSnowflakeDatabricksData EngineeringETLGitAgile

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