Analytics Engineer, Data Operations

Responsibilities

• Own the end-to-end design, implementation, and optimization of data pipelines and tables that support monitoring, reporting and analytics needs across Reality Mine.
• Work closely with technical and non-technical stakeholders to define metrics, model datasets, and ensure accuracy, scalability, and performance in our data ecosystem.
• 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).

• 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.
• Proactive and independent, with a focus on building future‑proof, maintainable solutions.

Demonstrates expertise in designing and optimizing scalable data pipelines and architecture, with a strong focus on SQL, Python, and cloud infrastructure such as AWS. Proven ability to collaborate with diverse stakeholders to ensure data accuracy, governance, and effective reporting.