Data Engineer II

You will be part of a small team focused on solving clearly defined problem spaces 
Build and maintain services and capabilities within our data platform to enable other teams
Create reliable and scalable data collection processes (i.e. streaming events and CDC-based), with attention to performance and cost
Share learnings, best practices and knowledge in order to promote business-wide data literacy
Collaborate with stakeholders to identify new opportunities, define requirements and deliver solutions
Define and document standards and policies in our data platform on subjects like CI/CD, governance and data processing.
Ensure our data is managed and secured in accordance with organisational policies

Technologies you’ll be working with
Google Cloud Platform (BigQuery, Pub/Sub, Dataflow, Dataproc)
Python
dbt
Apache Airflow
Terraform

What you’ll bring
You are

A team player and comfortable collaborating autonomously with multiple teams, systems and products in a dynamic environment
A problem solving mentality with strong attention to detail
Curious and always willing to learn
 

You have

2-5 years of industry relevant experience in data
Experience working with data transformation tools, e.g. dbt, Dataform
Experience with data modelling and data modelling techniques
Experience working in a cloud environment, GCP is highly preferred
Experience in a programming language (we use Python), proficient in SQL
A good understanding of data storage concepts like relational stores, columnar stores, partitioning, indexing
Experience with containerization and runtime environments (i.e. docker)
Good understanding of software development practices, including CI/CD, Git, Infrastructure as Code (Terraform)
Excellent written and verbal communication skills (English)
 

Nice to have

Experience managing and scaling large data models in dbt  – e.g. complex dependencies, multiple contributors, multiple dbt projects
Experience with data pipeline and workflow management tools such as Airflow
Experience on event based and/or distributed computing applications, i.e. Pub/Sub, Spark, Beam
Experience working with containerised applications at scale (i.e Kubernetes)