Senior Data and ML Engineer

• Design robust ingestion orchestration and integration architectures across ERP OT/IoT CAMs and SharePoint systems optimizing for scale cost resilience and security.

• Own the enterprise data model and SSOT design to ensure consistency across business domains.

• Establish and enforce core engineering standards (testing CI/CD pipelines release and rollback protocols) via rigorous code reviews.

• Architect MLOps frameworks and ML data pipelines defining standard patterns for algorithm development and library usage.

• Design integration patterns to power ML models using operational (AVEVA PI) and asset management data.

• Define and govern standards for the responsible adoption of AI and Generative AI tools.

• Own the technical architecture for AVEVA PI and CAMs ensuring high availability scaling and seamless upgrade planning.

• Set fleetwide Asset Framework (AF) modeling calculation and mapping standards driving analytics-led alerting and cross-site data integrity.

• Resolve complex cross-system architectural challenges and lead major incident reviews.

• Enforce enterprise data governance security and model risk standards.

• Align cross-divisional stakeholders and leadership on strategic technical decisions.

• Mentor engineers cultivate a culture of technical excellence and drive team capability in emerging technologies.

• Education: Bachelors degree in Computer Science Information Systems Engineering Mathematics or a related field.

• Experience: 710 years in data engineering or data platform development (minimum 6 years with demonstrated platform ownership at a Senior/Lead level).

• Technical Mastery: Advanced SQL and Python skills hands-on experience with ETL/ELT enterprise data modeling and scalable MLOps.

• Track Record: Proven experience leading platform architecture enforcing engineering standards and managing complex production environments.

• Data Engineering and Architecture: Expert-level SQL ETL/ELT pipelines data modeling and platform-wide architectural design.

• ML and AI Infrastructure: Advanced capability in MLOps production ML integration and AI readiness.

• OT and Asset Systems: In-depth technical mastery of AVEVA PI Asset Framework (AF) modeling and CAMs integration.

• Reliability and Governance: Strong focus on operational discipline system availability and risk management.

• Leadership: Proven ability to influence executive leadership align cross-functional teams and mentor junior engineers.

• Advantageous

  • Enterprise-level AVEVA PI architecture (HA upgrades AF modeling) in industrial/energy sectors.

  • Production ML frameworks (e.g. PyTorch TensorFlow) and orchestration tools (e.g. Azure Data Factory Airflow Prefect).

  • Cloud data lake/big data architectures and formal AI/ML governance frameworks.

Benefits:

Competitive salary based on experience (salary can potentially be more based on experience/skills)

IF you meet the above requirements and want to make a career-changing move apply today by emailing your CV to