Data Engineer (Core systems)

Requirements

• 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.