Experience in implementing reliable and performant ETL/ELT pipelines
Experience with version control systems (e.g., Git) for dbt project management
Knowledge of CI/CD pipelines for analytics workflows
Experience with programming languages such as Python
Familiarity with data governance practices and frameworks
Professional experience in analytics engineering / data analytics
Solid understanding of SQL with hands on experience with dbt and Snowflake
Comfortable implementing custom (in-house) data solutions where off-the-shelf products are unavailable or unsuitable
(Desirable) Advanced LookML knowledge
(Desirable) Experience using Pandas (TensorFlow, Scikit-learn, Matplotlib)
(Desirable) DevOps practices Docker and Kubernetes
(Desirable) Understanding of data science concepts
(Desirable) Professional experience or a degree in a quantitative field, such as Mathematics, Physics, Engineering, or Computer Sciences
What the job involves
You’ll join the Core Systems team, who are responsible for driving innovation across the business by optimising development, building data systems, and continuously improving iwoca products
We follow Agile-inspired processes, using continuous integration and delivery, so that features go live in days or weeks, not months or years
We are in the process of transitioning our entire analytics warehouse to Snowflake, from a federated SQL system to improve reliability and speed of accessing our wide data ecosystem
We run a variety of time consuming ETL tasks using libraries such as (NumPy, Scikit-learn, Pandas), and view/tables from a variety of relational databases
The aim is to integrate and transition all to a single data warehouse using Snowflake and dbt
We are looking for someone who has a solid amount of experience in analytics engineering, who can advise and implement high quality and reliable ETL/ELT processes to bridge the gap between data engineering and analytics
Who will collaborate with analysts, data scientists and engineers to deliver and improve our data warehouse and processes
You will have the opportunity to learn lots and develop rapidly, with the ability to influence critical data infrastructure
We are embarking on a transition to a data mesh operating model and are looking for a proactive, self-motivated individual to help drive this change
The successful candidate will identify opportunities to improve data processes, enable self-service access across the organisation, and design the governance frameworks and guardrails required to ensure data quality, security, and consistency
Develop, construct, test and maintain ETL/ELT infrastructure
Implement robust data testing frameworks in dbt to monitor and ensure data quality and integrity
Enable product teams to self-serve data more effectively, empowering them to make faster, more informed decisions
Influence and shape the monitoring, observability, and reliability strategy for the data warehouse, ensuring high availability, performance, and data quality
Partner with analysts, data scientists, and business stakeholders to understand data requirements and deliver actionable solutions
Troubleshoot emerging data and operational problems, and be a source of knowledge for end-users on the most appropriate way of using data for their purposes
Support your teammates by learning and sharing your knowledge
Drive knowledge sharing and capability building through mentoring, coaching, and the creation of educational resources and best practices
