Analytics Engineer

Description

• Collaboration with Stakeholders: Partner with analysts, scientists, and business teams to translate requirements into technical solutions.
• Performance Optimization: Enhance existing data processes for speed and scalability, ensuring efficient data processing.
• Data Transformation: Convert raw data from multiple sources into clean, reliable datasets for analysis and reporting, ensuring quality and consistency.
• Data Modelling: Develop and maintain logical and physical data models to support reporting and analysis needs, implementing best practices for data warehouse design.
• Data Pipeline Development: Design, build, and maintain robust, scalable, and efficient data pipelines using DBT, SQL, Python, and ETL frameworks.

Requirements

• Are a data engineer, analytics engineer, software engineer, or technical data analyst with a passion for data modelling and transformation.
• Are comfortable in an agile environment using Terraform, CI/CD, pair programming, and deployment strategies.
• Have experience delivering analytical solutions (e.g. in the Databricks stack).
• Can orchestrate complex data pipelines.
• Enjoy building scalable, resilient analytical products.
• Possess data modelling expertise using tools such as DataForm or DBT.
• Have experience with streaming technologies (Kafka Streams, Amazon Kinesis or similar) for sourcing and transforming large-scale data.

Benefits

• Seek continuous learning opportunities to deepen or broaden your knowledge.

Training + Development

Interview process

Visa Sponsorship

Security clearance