Data Architect

We are looking for an experienced Data Architect / Engineering Lead to take ownership of designing and building modern data ecosystems supporting advanced technologies, AI initiatives, automation, and large-scale analytics. This is a strategic and hands-on role for someone who enjoys shaping architecture from the ground up while actively contributing to implementation.

• Strong commercial experience in data architecture and data engineering within complex environments
• Hands-on expertise in modern data pipelines, integration frameworks, and distributed processing
• Experience with cloud-based data platforms and large-scale data ecosystems
• Good understanding of batch, streaming, and event-driven architectures
• Experience designing data models for both operational and analytical purposes
• Knowledge of APIs, interoperability standards, and system integration approaches
• Experience working with machine, telemetry, sensor, or operational data is highly valued
• Ability to combine strategic architecture ownership with hands-on implementation
• Strong communication skills and confidence working with both technical and business stakeholders

Nice to have:

• Experience in innovation-driven, industrial, infrastructure, engineering, or highly regulated environments
• Familiarity with edge-to-cloud architectures, digital twins, simulation environments, or AI-ready platforms
• Exposure to metadata management, governance, and lineage solutions

• Define and drive end-to-end data architecture, including ingestion, storage, transformation, integration, and consumption layers
• Design and implement scalable data pipelines supporting structured, semi-structured, unstructured, and real-time data
• Build integration patterns across enterprise applications, devices, APIs, operational systems, and third-party environments
• Develop canonical data models enabling interoperability between fragmented systems and business domains
• Support AI, analytics, automation, and data product initiatives through reliable and scalable data foundations
• Establish engineering standards, DataOps practices, monitoring, and quality controls
• Collaborate with security and governance teams to ensure data quality, lineage, access control, and compliance requirements
• Lead technical decisions regarding platforms, architecture direction, and implementation strategy
• Provide technical leadership while remaining actively involved in engineering delivery