Analytics Engineer | Manager

Role Overview

The Analytics Engineer is accountable for turning Managed Services Technology data into trusted, reusable data products that support delivery decisions, service operations, and executive reporting.

What You Will Do

Analytics data modelling and transformation, metric, KPI and semantic layer ownership, data quality, testing and observability, reporting, insight and decision support, AI-enabled and automation-aware analytics.

Why It Might Be a Fit

Strong experience in analytics engineering, data modelling, BI engineering, data analysis, data engineering or a similar modern data role, advanced SQL experience, practical experience building trusted analytical datasets in cloud data warehouse or lakehouse environments.

Requirements

• Strong experience in analytics engineering, data modelling, BI engineering, data analysis, data engineering or a similar modern data role.
• Advanced SQL experience and practical experience building trusted analytical datasets in cloud data warehouse or lakehouse environments.
• Experience with data transformation frameworks, version control, code review, CI/CD, testing, documentation and analytics lifecycle management.
• Experience defining KPIs, semantic layers, metric catalogues, business glossaries, dashboards or governed self-service reporting assets.
• Experience working with operational, workflow, service management, product, AI, automation or managed service data preferred.
• Experience with Python, dbt or equivalent transformation tooling, BI platforms, data observability, data catalogues or lineage tools preferred.

Benefits

• Leadership development programs and executive coaching designed to help you inspire teams and accelerate your career growth.
• A culture valuing diverse perspectives, empowering leaders to drive innovation and collaboration.
• A world-class parental leave policy offering up to 26 weeks of leave for caregivers, supporting your family and personal life.
• Flexibility means trusting you to choose when, where, and how you work, balancing what’s best for you, your team, and your clients to grow and thrive together.

Tagged as: Data Analysis, Python, SQL