Data Engineer

Nasstar

28d•Remote

About The Position

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.

Requirements

3+ years of commercial experience delivering production data engineering solutions.
Strong hands-on experience with dbt is essential.
Proven experience developing data transformation models and implementing data modelling best practices using dbt.
Strong SQL skills.
Strong Python programming experience.
Commercial experience using Snowflake or Databricks as enterprise data platforms.
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.
Prior commercial experience delivering production data engineering solutions.

Nice To Haves

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.
Proven experience building data transformation models, implementing data modelling best practices and developing production-ready ELT pipelines using dbt.
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.

Responsibilities

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.