Data and Analytics Architect - L1

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world.

For additional information, visit us at www.wipro.com.

Job Description

Role Purpose The purpose of the role is to define and develop Enterprise Data Structure along with Data Warehouse, Master Data, Integration and transaction processing with maintaining and strengthening the modelling standards and business information.

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Do

1. Define and Develop Data Architecture that aids organization and clients in new/ existing deals a. Partnering with business leadership (adopting the rationalization of the data value chain) to provide strategic, information-based recommendations to maximize the value of data and information assets, and protect the organization from disruptions while also embracing innovation b.

Assess the benefits and risks of data by using tools such as business capability models to create an data-centric view to quickly visualize what data matters most to the organization, based on the defined business strategy c. Create data strategy and road maps for the Reference Data Architecture as required by the clients d. Engage all the stakeholders to implement data governance models and ensure that the implementation is done based on every change request e.

Ensure that the data storage and database technologies are supported by the data management and infrastructure of the enterprise f. Develop, communicate, support and monitor compliance with Data Modelling standards g. Oversee and monitor all frameworks to manage data across organization h.

Provide insights for database storage and platform for ease of use and least manual work i. Collaborate with vendors to ensure integrity, objectives and system configuration j. Collaborate with functional & technical teams and clients to understand the implications of data architecture and maximize the value of information across the organization k.

Presenting data repository, objects, source systems along with data scenarios for the front end and back end usage l. Define high-level data migration plans to transition the data from source to target system/ application addressing the gaps between the current and future state, typically in sync with the IT budgeting or other capital planning processes m. Knowledge of all the Data service provider platforms and ensure end to end view.

n. Oversight all the data standards/ reference/ papers for proper governance o. Promote, guard and guide the organization towards common semantics and the proper use of metadata

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p. Collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure a common understanding, consistency, accuracy and control q. Provide solution of RFP’s received from clients and ensure overall implementation assurance i. Develop a direction to manage the portfolio of all the databases including systems, shared infrastructure services in order to better match business outcome objectives ii. Analyse technology environment, enterprise specifics, client requirements to set a collaboration solution for the big/small data iii. Provide technical leadership to the implementation of custom solutions through thoughtful use of modern technology iv. Define and understand current issues and problems and identify improvements v. Evaluate and recommend solutions to integrate with overall technology ecosystem keeping consistency throughout vi. Understand the root cause problem in integrating business and product units vii. Validate the solution/ prototype from technology, cost structure and customer differentiation point of view viii. Collaborating with sales and delivery leadership teams to identify future needs and requirements ix. Tracks industry and application trends and relates these to planning current and future IT needs

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2. Building enterprise technology environment for data architecture management a. Develop, maintain and implement standard patterns for data layers, data stores, data hub & lake and data management processes b. Evaluate all the implemented systems to determine their viability in terms of cost effectiveness c. Collect all the structural and non-structural data from different places integrate all the data in one database form d. Work through every stage of data processing: analysing, creating, physical data model de