Responsibilities
- Design robust, secure, and supportable data solutions for both batch and streaming use cases, ensuring scalability, resilience, and security by design
- Develop, test, and support data pipelines integrating data from industrial, IoT, and enterprise systems using technologies such as Azure Synapse, and event streaming platforms (e.g. Event Hubs, Kafka, MQTT, Quix)
- Work with edge and integration platforms (e.g. HighByte, Ignition, Quix, or similar) to ingest, model, and standardise operational data, aligned to a Unified Namespace (UNS) approach for organising and distributing real-time operational data
- Build and optimise solutions for handling time-series and telemetry data, ensuring performance and usability at scale
- Collaborate with architects, cloud engineers, and platform teams to design and evolve data platform capabilities, including CI/CD, deployment automation, and environment management
- Ensure data quality, observability, and reliability across real-time and batch pipelines
- Where required, contribute to downstream data modelling and analytics to support reporting and insight
- Build automated test frameworks and develop test harnesses for each component, increasing overall test coverage and ensuring a culture of quality and reliability across the platform.
Qualifications
- Strong experience in data engineering using cloud platforms (e.g. Azure), including tools such as Azure Synapse, Spark, Python, and SQL
- Experience working with real-time or streaming data pipelines (e.g. Event Hubs, Kafka, MQTT, Quix, or similar)
- Experience working with time-series or telemetry data
- Experience integrating data from APIs, industrial systems, or edge platforms (e.g. HighByte, Ignition, or similar)
- Familiarity with Unified Namespace (UNS) principles and MQTT-based architecture is advantageous
- Experience in data modelling (e.g. relational modelling, dimensional modelling, or similar approaches suited to operational systems)
- Experience delivering end-to-end data solutions from ingestion through to production deployment
- Experience working in an Agile/Scrum environment
- Experience collaborating with platform and engineering teams to support CI/CD, DevOps, and engineering best practices
- Knowledge of Azure DevOps or similar tools
- Awareness of security, data governance, and working within regulated or operationally critical environments is desirable.
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