Business Intelligence Engineer

Accountabilities

• • Design, build, and maintain robust data pipelines, data warehouse infrastructure, and data lake environments using AWS services.
  • Establish reliable and scalable data flows across business systems while maintaining high standards for data quality, availability, and consistency.
  • Optimise data infrastructure for performance, reliability, scalability, and effective data governance.
  • Develop and maintain data models and transformation processes that support reporting, analytics, and business intelligence use cases.
  • Build high-quality, intuitive, and actionable dashboards in Looker or comparable business intelligence platforms.
  • Work closely with business stakeholders to understand operational requirements, define KPIs, and translate business questions into effective analytical solutions.
  • Explore and analyse datasets to identify trends, patterns, opportunities, and areas for operational or commercial improvement.
  • Partner with leadership to deliver data-driven analysis that supports strategic decision-making and measurable business change.
  • Translate complex analytical findings into clear, concise, and actionable recommendations for technical and non-technical audiences.
  • Continuously improve the data stack, reporting environment, and analytical processes to increase the accessibility and business value of data.
  • Take end-to-end ownership of business intelligence initiatives, from underlying data pipelines through dashboards and actionable insights.

  Requirements

  • Strong professional experience with Python and SQL, with the ability to develop reliable data transformation and analytical workflows.
  • Hands-on experience with AWS data services, particularly Amazon Redshift, S3, Glue, Athena, and Lambda.
  • Proven ability to design, model, transform, and visualise data effectively.
  • Experience building and maintaining dashboards in Looker or a comparable BI platform.
  • Solid understanding of data warehousing, data lakes, data pipelines, and modern data architecture principles.
  • Ability to work across the data stack and take ownership from data ingestion and transformation through reporting and business analysis.
  • Strong analytical mindset with the ability to identify meaningful patterns, trends, and commercial opportunities within complex datasets.
  • Commercial awareness and the ability to distinguish between data that is technically interesting and data that is genuinely valuable to the business.
  • Excellent communication skills, with the ability to explain complex analytical concepts clearly and tell compelling stories with data.
  • High attention to accuracy, clarity, reliability, and detail.
  • Self-directed and comfortable working with significant autonomy in a small, fast-paced environment.
  • Collaborative approach and ability to work effectively with stakeholders across technical, operational, and leadership functions.
  • Availability to work fully remotely, ideally within approximately ±2 hours of GMT.

  Benefits

  • Fully remote working opportunity.
  • Competitive compensation.
  • Significant ownership across the end-to-end data and business intelligence stack.
  • Opportunity to work with modern AWS data technologies and business intelligence tooling.
  • Direct exposure to leadership and the ability to influence important business decisions through data.
  • Small, fast-moving, ambitious team with minimal bureaucracy and clear individual ownership.
  • Opportunity to shape data infrastructure, reporting practices, and analytics capabilities from an early stage.
  • High-impact environment where your work can directly influence business strategy, operations, and growth.