The Director of Data and Analytic Solution Architecture will combine his / her technical and business domain expertise to translate complex business requirements into elegant, scalable, and optimized Data and Analytic solutions.
The ideal candidate will have a deep expertise in applying cloud native technologies to solve complex data and analytic problems, a familiarity with enterprise reporting tools, and significant experience in working with a variety of data sets and structures within a large global enterprise.
They will ensure the technical feasibility, alignment to business requirements, and support the full lifecycle of solutions across the Data & Analytics portfolio.
Additionally, they are strong collaborators partnering with a variety of key stakeholders across the organization including Business Intelligence & Analytics, IT, InfoSec.
They are champions of enterprise standards working closely with our Enterprise Architecture and Enterprise Data Management teams to drive adoption and rationalization of enterprise platforms, tools, and data.
Functional Capabilities :
Broad and deep understanding of data and analytics capabilities in a global enterprise across all process areas (Supply Chain, Finance, Marketing, R&D etc.
Familiarity and expertise in working with data across a variety of sources including SAP, POS, external 3rd party, social media, IOT, etc.
Ability to understand and synthesize complex concepts and problems into simple, reusable, scalable, and elegant solutions.
Defines and enforces architecture patterns and standards on optimized, available, reliable, consistent, accessible platforms and tools.
Flexible and open mindset : Sees challenges and problems as opportunities to grow. Understands there are multiple ways to solve a problem, respects and listens to multiple opinions, and continuously evaluates and challenges assumptions.
Strategic Thinking : Aligns strategy of the solution with overall company and department goals.
Establishes clear objectives, assigns responsibilities, and takes accountability.
Strong communications skills to collaborate with the virtual global team
Results-driven sets aggressive goals and delivers through the team
Pragmatic approach to deliver incremental value to the organization
Comfortable operating within a global, complex, highly matrixed organization
Well-developed team management skills
Proven ability to attract, retain, and develop talent
Strong problem solving and analytical skills
Ability to establish credibility and be decisive but able to recognize and support the organization’s preferences and priorities.
Technical Competencies :
Detailed conceptual and technical understanding of building data and analytic capabilities in a cloud native environment.
Experience on Azure preferred, with focus on building serverless architectures.
Expertise in data platforms (Data Lake, Data Warehousing, Graph DB, NoSQL, etc.) and integration ingestion patterns (ETL, ELT, API, streaming, etc.)
Expert in visualization tools such as Tableau, PowerBI, SAP Business Objects
Expert understanding of Data as a Service concepts including APIs / web services and microservices
Experience in defining semantic and / or virtualization layers, metadata to support technical and business teams for development and data consumption
Strong understanding of Data Science and Machine Learning (ML) concepts and how to operationalize models in a data platform (experience with Azure ML components preferred).
Strong understanding of data modeling concepts; hands-on data modeling expertise desired (preferably in ERwin)
Collaborate with product teams, data analysts and data scientists to design and build data-driven solutions that meet ELC’s quality standards
Accountable for collaborating with global team on business requirements, identifying solution gaps and available capabilities, and defining solutions to meet the business need
Translates business domain understanding and context to technical capabilities for technical architects and development teams
Develop data catalogs and data validations to ensure clarity and correctness of key business metrics
Build and maintain dimensional data warehouses in support of business intelligence tools
Define full life cycle and roadmap of data product : from experimentation, to implementation, deployment and maintenance
Partner with System of Record owners, integration teams, development teams, data modeling teams to implement data products
Partner with Enterprise Data Management and Data Governance functions to ensure scope, validity, accuracy and completeness of core Enterprise Data Sets.
Collaborate with Enterprise Architecture to shape EA guardrails, standards and patterns
Ensure alignment with Enterprise Architecture principles, guardrails, standards, patterns and frameworks
Stay abreast of current trends / technologies in consumer space and be aware of technology initiatives from other best in class retailers and technology companies globally
Manage Stakeholder’s concerns regarding technical issues for their areas