Full Description

About the Role We are looking for a data-focused engineer to build confidence, traceability, and reliability into an algorithm-driven product. This role sits at the intersection of data engineering, algorithm validation, and product analytics, ensuring that data pipelines and machine-learning outputs are testable, auditable, and reproducible over time.

You will work closely with software engineers, data scientists, and business stakeholders to embed robust testing and validation practices across the data and algorithm lifecycle — a critical capability for regulated, production-grade systems. What You’ll Do

1. Build and own data & algorithm validation tests

• Design and implement unit tests across data pipelines and engineered features, covering multiple stages of data collection, transformation, and consumption.
• Create validation tests for inputs to and outputs from algorithms, including black-box machine learning models.
• Ensure test coverage supports correctness, completeness, and consistency of algorithmic behaviour.
• Establish repeatable test execution processes and document outcomes as part of the product release lifecycle.

2. Enable reproducibility and auditability of algorithm outputs

• Implement mechanisms to snapshot and archive algorithm inputs, features, and outputs, enabling recreation of historical predictions at any point in time.
• Define and communicate data and logging requirements to the broader software engineering team.
• Support traceability requirements commonly expected in regulated or compliance-sensitive environments.

3. Support analytics and operational reportingPartner with analytics and business teams to ensure daily and weekly reporting pipelines are reliable and validated, including metrics related to data completeness, user engagement, and algorithm actions.

• Diagnose and resolve data quality issues impacting downstream reporting and decision-making.
• What You Bring
• Bachelor’s degree in Computer Science, Engineering, Business Analytics, or a related discipline.
• 2+ years of experience in data engineering, analytics engineering, or data-centric product roles.
• Strong ability to implement automated tests in Python, particularly for data and algorithm validation.
• Solid understanding of data quality, validation, and reproducibility requirements for algorithmic products.
• Experience working alongside software engineers and data scientists in production environments.
• Exposure to healthcare, regulated industries, or audit-driven systems is a strong advantage.
• Why This Role Matters