10 Sep
|
ACL Digital
|
Pune
About the RoleExperienced 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 robust 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.QualificationsProven 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.
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