Analytics Engineer, Data Operations

Responsibilities

• ● RealityMine has been a pioneer in delivering data driven insights to the world's largest brands for over a decade. Our platform provides unique data solutions to our clients enabling them to make strategic, informed decisions powered by data from real people, collected in a privacy safe way.
• ● We are seeking an Analytics Engineer to join our Data Operations function. This role focuses on building and maintaining scalable data pipelines, curated datasets, and robust architecture that underpins analytics, monitoring, and reporting across the business.
• ● As an Analytics Engineer, you will own the end-to-end design, implementation, and optimization of data pipelines and tables that support monitoring, reporting and analytics needs across RealityMine. You will work closely with technical and non-technical stakeholders to define metrics, model datasets, and ensure accuracy, scalability, and performance in our data ecosystem. This role requires strong technical skills, problem-solving ability, and a business-focused mindset to create solutions that are reliable, efficient, and future-proof.
• ● Design and build scalable data pipelines and tables to support analytics, monitoring, and reporting.
• ● Collaborate with stakeholders to define, validate, and standardise business metrics.
• ● Implement medallion-style data architecture, ensuring clear lineage, governance, and scalability.
• ● Optimise data pipelines for performance, reliability, and maintainability.
• ● Ensure data accuracy, completeness, and consistency across our data.
• ● Contribute to best practices for SQL, PySpark, and workflow scheduling (e.g. Airflow, Azkaban).
• ● Work with stakeholders to understand requirements and translate them into technical solutions.
• ● Support the adoption of self-serve analytics by providing well-modelled, trusted datasets.
• ● Adhering to Company Policies and Procedures with respect to Security, Quality and Health
• ● Here's what we're looking for:
• ● Proficiency in SQL and Python, with experience in distributed data processing.
• ● Experience designing and maintaining scalable data pipelines and architecture.
• ● Knowledge of cloud infrastructure, ideally AWS (e.g. Athena, S3, Glue).
• ● Understanding of medallion architecture and principles of data modelling, lineage, and governance.
• ● Familiarity with workflow scheduling tools such as Azkaban or Airflow.
• ● Excellent problem-solving skills and attention to detail.
• ● Ability to collaborate effectively with technical and non-technical colleagues.