Business Insights Platform Engineer

Description

As a Business Insights Platform Engineer, you will be central to Unilode's self-service strategy. Reporting to the Business Insights Manager, your role is to drive and support the adoption of self-serve analytics internally and with our customers. Working with analysts, BI engineers, and stakeholders across the business to craft impactful data products that reduce time-to-insight and improve decision-making for Unilode and our customers.

You will help shape the semantic layer, ensuring it serves as a platform-agnostic, single source of truth that powers our growing suite of data products and supports the generation of insights. This is more than a visualization role; it’s a business transformation role. While your immediate focus is on the adoption of Power BI, you will also lead the evaluation of next-gen analytics technologies to ensure our BI platform evolves with the changing needs of our business.

Key Responsibilities

Product Strategy & Ownership

Ownership & Accountability | Strategic Thinking | Commercial Awareness

• Own, maintain, and communicate the Business Insights data product roadmap, ensuring clear prioritisation aligned to business strategy.
• Translate organisational goals, customer needs, and market insights into a coherent and forward looking product direction.
• Establish clear KPIs and measurable success metrics to ensure outcomes are tracked and reported transparently.
• Take full accountability for the BI platform end-to-end, including user management, scalability, adoption, semantic model design, performance optimisation, and long-term sustainability.

Feature Planning & Execution

Delivery Excellence | Structured Problem Solving | Quality Focus

• Translate business requirements into structured product documentation, including workflows, user stories, and defined acceptance criteria.
• Ensure high release standards by clearly defining quality thresholds and validation processes.
• Partner with design stakeholders to deliver intuitive, self-serve, automation-led user experiences that scale effectively.
• Support engineering and data teams throughout the development lifecycle, proactively removing blockers and ensuring delivery against roadmap commitments.

Customer & Stakeholder Engagement

Stakeholder Management | Communication | Influence

• Conduct structured user research, stakeholder interviews, and feedback analysis to ensure product relevance and continuous improvement.
• Collaborate closely with Customer Success teams to align product evolution with real-world usage and client needs.
• Lead Product Steering Committees, providing clear updates, managing expectations, and influencing decision-making at the leadership level.

Cross-Functional Collaboration

Collaboration | Leadership Without Authority | Alignment & Transparency

• Work closely with software engineering, data engineering, analytics, and operations teams to ensure cohesive execution.
• Drive alignment across product, engineering, and commercial functions, ensuring shared objectives and coordinated delivery.
• Champion structured planning, prioritisation frameworks, and transparent communication to support scalable ways of working.

User Analytics & Insights

Data-Driven Decision Making | Continuous Improvement | Innovation

• Lead the implementation of product analytics frameworks to measure adoption, engagement, and user journeys.
• Analyse behavioural and performance data to inform roadmap decisions and iterative feature improvements.
• Drive increasingly data-led product evolution by leveraging AI and automation capabilities to autogenerate scalable, actionable insights.

Our Values in Action:

• Be humble and curious: Continuously seeks to understand business context, data behaviour, and technical improvements.
• Inspire, empower, and prosper: Builds confidence in analytical outputs through reliability, clarity, and professional conduct.
• Team up to be better: Works collaboratively across technical and business teams to deliver aligned outcomes.
• Be passionate about our customers: Focuses on delivering products and capabilities that create measurable operational and business value.
• Take ownership and get things done: Takes responsibility for delivering complete, high-quality solutions from start to finish.
• Be eager to win: Strives for impact through the launching and landing of compelling data products.
• Build a better future: Contributes to stronger data practices, scalable systems, and improved self-serve analytical capability over time.

The Small Print

A customer-obsessed, data product expert with a strong commercial instinct, empathy, and the ability to connect deeply with both external customers and internal teams—while maintaining a high bar for delivery quality. Driving a culture change of self-serve analytics by designing and managing a suite of products and the underlying BI platform.

This document outlines the key responsibilities and expectations of the role, but it is not exhaustive. Responsibilities may evolve in line with business priorities, technological developments, and the organisation's analytical maturity. The role requires a high level of autonomy, the ability to think clearly in ambiguous situations, and strong personal accountability for deliverables and outcomes.

Requirements

Qualifications & Experience

• Data product development.
• Experience with product management and delivery.
• Solid experience in working with BI tools (preferably PowerBI)
• Proven ability to work with engineering, data, design, and commercial teams.
• Strong commercial awareness and understanding of customer-centric design.
• Experience in gathering requirements, writing user stories, and managing product roadmaps.
• Strong Go-to-Market understanding with experience of writing/maintaining product definitions, user guides, and rollout delivery.
• Proficiency in SQL.
• Solid understanding of data modelling fundamentals.
• Strong analytical and structured problem-solving skills.
• Ability to independently drive analytical projects from requirement clarification to delivery.
• Strong communication and stakeholder management skills.
• Experience using Databricks or similar cloud-based data lakehouse platforms.
• Experience with PySpark, Python, Git.
• Experience in embedded analytics techniques.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
• Understanding of AI and potential use cases.
• Experience in aviation, logistics, or operational systems.