Analytics Engineer, Data Operations

RealityMine

Analytics Engineer managing the design and optimization of data pipelines at RealityMine. Collaborating with stakeholders to ensure accurate and scalable data solutions.

Posted 7/18/2026full-timeManchester • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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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.

Highest-signal resume keywords

SQL ProficiencyPython ProgrammingData Pipeline DesignAWS Cloud InfrastructureMedallion Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData Pipeline DesignDistributed Data ProcessingData ModellingData LineageData GovernancePerformance OptimizationScalabilityData Accuracy

Soft Skills

Problem-SolvingAttention to DetailCollaborationProactive ApproachIndependence

Tools & Technologies

AirflowAzkabanAWS AthenaAWS S3AWS Glue

Industry Keywords

Data EcosystemMonitoringReportingAnalyticsWorkflow Scheduling

Tech Stack

Tools & technologies

AirflowAWSCloudPySparkPythonSQL

About the role

Key responsibilities & impact

Own the end-to-end design, implementation, and optimization of data pipelines and tables that support monitoring, reporting and analytics needs across RealityMine.
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).

Requirements

What you’ll need

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.

Benefits

Comp & perks

Free parking and secure bike shed.
Excellent public transport links.
Split your time between the office and home.
Flexible start and finish times to suit your personal circumstances.
Fully stocked kitchen with wide range of snacks and monthly Team lunches.