GCP Data Engineer
Role details
Job location
Tech stack
Job description
While our broker platform is the core technology crucial to Ki's success - this role will focus on supporting the middle/back-office operations that will lay the foundations for further and sustained success. We're a multi-disciplined team, bringing together expertise in software and data engineering, full stack development, platform operations, algorithm research, and data science. Our squads focus on delivering high-impact solutions - we favour a highly iterative, analytical approach.
You will be designing and developing complex data processing modules and reporting using Big Query and Tableau. In addition, you will also work closely with the Ki Infrastructure/Platform Team, responsible for architecting, and operating the core of the Ki Data Analytics platform.
What you will be doing: ️
- Work with both the business teams (finance and actuary initially), data scientists and engineers to design, build, optimise and maintain production grade data pipelines and reporting from an internal Data warehouse solution, based on GCP/Big Query
- Work with finance, actuaries, data scientists and engineers to understand how we can make best use of new internal and external data sources
- Work with our delivery partners at EY/IBM to ensure robustness of Design and engineering of the data model/ MI and reporting which can support our ambitions for growth and scale
- BAU ownership of data models, reporting and integrations/pipelines
- Create frameworks, infrastructure and systems to manage and govern Ki's data asset
- Produce detailed documentation to allow ongoing BAU support and maintenance of data structures, schema, reporting etc.
- Work with the broader Engineering community to develop our data and MLOps capability infrastructure
- Ensure data quality, governance, and compliance with internal and external standards.
- Monitor and troubleshoot data pipeline issues, ensuring reliability and accuracy.
Requirements
Experience designing data models and developing industrialised data pipelines
- Strong knowledge of database and data lake systems
- Hands on experience in Big Query, dbt, GCP cloud storage
- Proficient in Python, SQL and Terraform
- Knowledge of Cloud SQL, Airbyte, Dagster
- Comfortable with shell scripting with Bash or similar
- Experience provisioning new infrastructure in a leading cloud provider, preferably GCP
- Proficient with Tableau Cloud for data visualization and reporting
- Experience creating DataOps pipelines
- Comfortable working in an Agile environment, actively participating in approaches such as Scrum or Kanban
Desirable Skills
- Experience of streaming data systems and frameworks would be a plus
- Experience working in regulated industry, especially financial services would be a plus
- Experience creating MLOps pipelines is a plus