Intermediate Analytics Engineer

Role Overview

As an Intermediate Analytics Engineer, you will design, implement, and optimise analytics data models and pipelines. You’ll be responsible for developing robust, scalable solutions that enable high-quality business intelligence and analytics.

Key Responsibilities

• Design and implement relational, multi-dimensional, and domain-specific semantic models. Apply data normalisation principles.
• Develop and optimise analytics pipelines using dbt, SQLMesh, and similar tools.
• Implement and monitor data quality frameworks (dbt tests, SodaCL) to ensure reliable datasets.
• Integrate and transform data from diverse sources for analytics consumption.
• Write efficient SQL and Python code for data transformation and analysis.
• Develop dashboards and reports in Power BI and Excel.
• Work with data analysts, engineers, and business stakeholders to gather requirements and deliver solutions.
• Maintain comprehensive documentation of data models, pipelines, and processes.
• Use Git and Azure DevOps/GitHub for version control, pull requests, and CI/CD pipeline management.
• Apply knowledge of open table formats (Delta, Hudi, Iceberg), open lakehouse concepts, open catalogs (Unity Catalog), and data sharing protocols (Redshift Share, Delta Sharing).
• Understand and contribute to data mesh concepts and goals.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or related field.
• Proven experience in analytics engineering or data analytics.
• Strong proficiency in SQL, Python, and data modeling.
• Experience with dbt, SQLMesh, and data quality frameworks.
• Familiarity with BI tools (Power BI, Excel).
• Experience with version control (Git) and CI/CD pipelines.
• Understanding of open table formats, lakehouse concepts, and data mesh principles.
• Strong analytical, problem-solving, and communication skills.

Preferred Skills

• Certification in analytics engineering or cloud technologies.
• Experience with cloud platforms (Azure, AWS, Google Cloud).
• Knowledge of software engineering best practices.
• Familiarity with open catalogs and data sharing protocols.