Senior Solutions Architect

About the Role

Experienced Senior Solution Architect – Data to lead the design and governance of enterprise-wide data platforms and analytics solutions. Lead design and optimisation of the data ecosystem for a large engineering enterprise with a diverse application landscape that includes multiple ERPs (Baan, Oracle, SAP), cloud platforms, and SaaS solutions. Demonstrated technical expertise with strong architectural leadership are a must for the role.

Responsibilities

• Define and govern the enterprise data architecture, ensuring alignment with business strategy and IT standards.
• Design end-to-end data solutions across ingestion, storage, modelling, analytics, and governance layers, especially focussed on leveraging Azure and Databricks as strategic platforms.
• Develop strategies to unify data from multiple ERPs (Baan, Oracle, SAP) and cloud/SaaS systems into a data lake platform.
• Establish information architecture, metadata management, and data quality frameworks.
• Collaborate with business stakeholders, and development teams to translate requirements into scalable technical solutions.
• Provide thought leadership on emerging data technologies and how they can create business value.
• Support governance processes for change management, security, compliance, and lifecycle management of data assets.

Qualifications

Proven track record as a Data/Analytics Solution Architect in complex enterprise environments with experience in data modelling, warehousing, and information architecture.

Required Skills

• Experience architecting solutions using Azure data services and Databricks (e.g., Synapse Analytics, Data Lake, Azure SQL, Data Factory, Spark, and Delta Lake) for large-scale data engineering and advanced analytics.
• Experience in implementing data governance, security, and regulatory compliance practices.
• At least 7 years of experience of architecting on premise and cloud data solutions in Finance and Supplychain domains.

Preferred Skills

• Exposure to advanced analytics, AI/ML solutions, or IoT data integration.
• Experience with API-led integration and event-driven architectures.
• Knowledge of industry-specific data standards.