Réalta Technologies is searching for a Senior Data SME to build, design and implement the data foundation required to deliver the 2026 Digital Strategy for our client in the Medical Device industry. This role will operate at a senior developer level and will be responsible for transforming fragmented operational data into a governed, scalable, near real-time analytics ecosystem.

The successful candidate will drive end-to-end data solution delivery, from data ingestion and modelling to dashboard engineering and automation, with a strong focus on manufacturing performance metrics (OEE, downtime, WIP, throughput, and inventory absorption). This is a hands-on technical leadership role requiring deep expertise in data modelling, system integration and data architecture.

Job Responsibilities

• Enterprise Data Architecture: Design and implement scalable analytical data models and system integrations to support advanced analytics, machine learning, and operational intelligence.
• Data Pipeline & Processing Engineering: Build and optimize robust batch and near real-time data pipelines, including time-series processing, window aggregations, and query performance tuning.
• Advanced Analytics & Machine Learning: Develop, deploy, monitor, and optimize end-to-end machine learning models, incorporating anomaly detection, signal smoothing, and statistical analysis techniques.
• Manufacturing & Operational Analytics: Lead the development of analytics frameworks covering OEE, downtime modeling, cycle time variance, throughput, WIP flow, inventory absorption, and lead-time adherence.
• Enterprise Power BI & Semantic Modeling: Develop enterprise-grade Power BI datasets and optimized semantic models using advanced DAX, calculation groups, RLS, and performance optimization techniques.
• Reporting Architecture & Governance: Design scalable reporting frameworks including KPI alerting, drill-through logic, deployment pipelines, version control, and dataset reuse governance.
• Data Governance & KPI Standardization: Define standardized KPI frameworks, implement validation and quality controls, and align metric definitions across cross-functional stakeholders.
• Senior Technical Leadership: Operate autonomously, translate ambiguous business problems into structured data solutions, influence senior stakeholders, and balance rapid delivery with architectural integrity.