About the position
Role Purpose:
The Senior Analytics Engineer is responsible for designing and leading the development of scalable, high-quality analytics data platforms that enable advanced analytics, business intelligence, and AI use cases. This role plays a strategic function in defining data modelling standards, ensuring data reliability, and aligning analytics engineering practices with organisational data strategy. The role also provides technical leadership and mentorship within the analytics engineering function, ensuring best practices, consistency, and continuous improvement across the data lifecycle.
RequirementsMinimum
- Bachelor’s degree in Data Science, Statistics, Computer Science, Information Systems, Engineering, or related field.
- 5+ years of experience in analytics engineering, data engineering, or advanced analytics roles.
- Expert-level proficiency in SQL and extensive experience designing scalable analytical data models.
- Strong experience with data transformation tools (e.g., dbt) and modern data warehouses (e.g., BigQuery, Snowflake, Redshift).
- Deep understanding of data modelling concepts (star schema, dimensional modelling, data vault, fact/dimension design).
- Proven experience working with BI tools (Power BI, Tableau, Looker etc.) and enabling self-service analytics.
- Strong experience with version control systems (e.g., Git) and CI/CD practices in data workflows.
Responsibilities
Analytics Data Modelling & Architecture
- Lead the design, development, and optimisation of scalable analytics data models and data layers.
- Define and enforce modelling standards, best practices, and architectural patterns across the organisation.
- Ensure consistent, reusable, and well-governed definitions of metrics, dimensions, and business logic.
Data Quality, Reliability & Observability
- Establish and oversee robust data quality frameworks, testing strategies, and monitoring systems.
- Ensure reliability and performance of data pipelines and analytical models at scale.
- Drive root cause analysis and resolution of complex data issues across upstream and downstream systems.
Enablement of Advanced Analytics & BI
- Partner with data scientists, analysts, and BI teams to enable advanced analytics and AI use cases.
- Design data models that support scalability, performance, and flexibility for diverse analytical needs.
- Champion self-service analytics by creating well-structured, accessible, and performant datasets.
Leadership, Governance & Standards
- Define and implement analytics engineering standards, governance frameworks, and best practices.
- Lead documentation initiatives for data models, definitions, and lineage.
- Ensure compliance with data governance, security, and regulatory requirements.
Stakeholder Engagement & Strategy
- Collaborate with business and technical stakeholders to align data models with strategic objectives.
- Translate complex business requirements into scalable and maintainable data solutions.
- Contribute to data platform strategy, roadmap, and tooling decisions.
Mentorship & Team Development
- Mentor and guide junior and mid-level analytics engineers.
- Conduct code reviews and provide technical oversight.
- Foster a culture of continuous learning, collaboration, and excellence.
Role Competencies
Technical
- Expert-level SQL and advanced data modelling expertise.
- Deep experience with modern data stack tools and architectures.
- Strong understanding of data pipelines, orchestration, and dependencies.
- Familiarity with software engineering best practices in data (CI/CD, testing, modular design).
Analytical & Problem-Solving
- Ability to design scalable solutions to complex data challenges.
- Strong critical thinking and data validation skills.
- Proactively identifies risks, inefficiencies, and improvement opportunities.
Communication & Collaboration
- Strong stakeholder management and communication skills.
- Ability to translate technical concepts into business-friendly insights.
- Produces high-quality documentation and promotes knowledge sharing.
Leadership & Influence
- Demonstrates technical leadership and decision-making capability.
- Influences data strategy and promotes best practices across teams.
- Builds alignment across cross-functional teams.
Adaptability and Agility
- Thrives in dynamic, fast-paced environments.
- Continuously evolves tools, practices, and skillsets.
- Drives innovation in analytics engineering approaches.
Desired Skills:
- SQL
- SnowFlake
- BigQuery
- BI Tools
- Git
- CI/CD
- AI
Desired Qualification Level:
About The Employer:
