Job description
We are looking for Analytics Engineers who can transform raw and fragmented data into reliable, well-structured and reusable data products.
This position combines analytics, data engineering and data-quality responsibilities. You will use SQL, Python and AI-assisted tools to build dependable datasets, automate recurring work and make data easier for analysts and business teams to understand and use.
We value a strong data-organization mindset: clear definitions, consistent naming, documented ownership, traceable lineage, automated quality checks, version control and reproducible work.
Responsibilities
- Understand business requirements and translate them into appropriate data models and technical solutions.
- Build and maintain clean, reusable analytical datasets and data models.
- Develop SQL and Python workflows for data transformation, validation, reconciliation and automation.
- Convert recurring manual processes into tested and reproducible workflows.
- Establish automated checks for data completeness, freshness, consistency and accuracy.
- Investigate data-quality issues and coordinate with relevant teams to resolve their root causes.
- Maintain data dictionaries, metric definitions, lineage documentation and naming standards.
- Apply version control, testing and code-review practices.
- Improve the accessibility and discoverability of trusted data.
- Support analysts and business users in using data correctly and consistently.
- Communicate technical decisions, limitations and trade-offs to technical and non-technical stakeholders.
- Use approved AI agents to accelerate data exploration, coding, testing and documentation.
- Independently review AI-generated work and protect confidential or personal information.