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Shall be a key contributor to OSTTRA Data Strategy from technology & architecture point of view.
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The role shall lead and own the definition of OSTTRA Enterprise Data Architecture blueprint. Blueprint would inform the data architecture & roadmap including for any horizontal and platform level capabilities and those of key business programmes.
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The scope of the role shall cover the front to back of the data architecture patterns including for data acquisition, mastering, data storage & organisation patterns, data processing, data distribution and consumption patterns.
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Design, implement, and manage cloud-native data lakes, ensuring data quality, security, and governance.
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This role shall partner closely with BI and AI delivery teams to enable them with the right data architecture patterns and inputs.
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Data Modelling: Develop and maintain enterprise data models for consistency and interoperability.
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The individual will be a member of OSTTRA Architecture Board & contribute to overall Architecture Strategy in addition to progressing the Data Architecture Strategy & roadmap more specifically.
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Role shall be responsible for keeping the SME community engaged as part of build out of Data Architecture Strategy and practices; and shall keep wider community informed of the space.
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Role shall establish the technology, tooling and engineering practices needed for the implementation of various data architecture patterns. This would also include the practices related to content/data modelling, data management and data quality.
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It is required of this role to pursue a strong collaborative & partnership driven approach of working across security, infra, compliance/risk and delivery stake holders and organizations.
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Rich experience of leading Enterprise Data Architecture capabilities preferably for Financial Services Industry; including strong record of supporting rich programme deliveries across life cycle.
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Should have experience of articulating & championing the data architecture strategy, data practices, guidelines, and roadmaps for an enterprise from technology, architecture, platform, devops / engineering, and data lifecycle management point of view.
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Proven expertise in building and operating large-scale, cloud-native data lakes, with deep understanding of data lake architecture and hands-on experience with relevant cloud services.
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Rich experience of progressing cloud native data architecture preferably on GCP (Google Cloud Storage, Big Query, Dataflow, Dataproc, and related technologies) or else at least on one of the other cloud services providers (AWS, Azure, Snowflake)
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Rich expertise on essential and foundational data practices including MDM, data/message modelling, data quality management, data delivery lifecycle engineering practices etc.
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Rich expertise on various data architecture and implementation patterns across data lifecycle including data acquisition, mastering, data storage & organisation patterns, data processing, data distribution and consumption patterns.
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Rich expertise on common data technologies / approaches including relational databases, NOSQL, Object stores, Data lakes, Warehouses/Marts, ELT/ETL, messaging, streaming, replication, APIs etc.
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Rich expertise on app / business line / enterprise reporting patterns including BI, MIS, self-service.
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Awareness of enabling the ML & data analytics ecosystems through relevant data capabilities.
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Awareness of distributed & decentralised architectures including DLT, blockchain etc..
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Ability to translate business requirements and backlogs into solution architectures and roadmaps and to correlate cost and benefits cases of various deliverables and alternatives.
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Good interpersonal skills, teamwork, communication, collaboration, facilitation, and negotiation.
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A candidate with overall 16-20 years of experience in IT industry with a robust track record of
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leading data architecture capabilities and initiatives in an independent decision-making capacity and demonstrated subject matter expertise in data technologies, architecture, and engineering spaces.