Director, Data Architecture

Position Summary...

What you'll do...

The Director of Health Data Analytics Architecture will be responsible for enhancing and optimizing the analytics & reporting architecture and platform to drive better business insights and improve the customer experience. This leadership position will require you work collaboratively with cross-functional teams and shape the future of our analytics capabilities. This position will report to the Senior Director of Data and Analytics in the Walmart Health & Wellness Digital Transformation Office.

This role is pivotal in driving our organization towards a data-driven future, ensuring that the analytics architecture and platform serve as a catalyst for better business insights and an enhanced patient experience. The person will lead the conceptual design and development of the H&W analytics data model, serving as the liaison between the technical staff and business stakeholders.

A successful candidate should be an analytics-minded, hands-on individual with a solid understanding of technical buildouts, strong leadership skills, entrepreneurial spirit and interest in healthcare. Curiosity and passion for automation, data management, digital data and new technologies, is a must. Primary day to day tasks will include working with teams across initiatives to gather requirements and information on workstreams which can be streamlined, developing complex buildout blueprints, coordinating technical work and communicating with key stakeholders.

You'll sweep us off our feet if...

You have extensive experience in data architecture and analytics with progressively responsible rolesYou have expertise in data warehousing, ETL processes, data modeling, and analytics toolsYou have a strong working knowledge of healthcare terminologies, including ICD-10, SNOMED, RxNorm, CPT/HCPCS, LOINC, and AthenaYou have familiarity with the HL7 FHIR and USCDI interoperability standards; and working knowledge of the OHDSI OMOP database and terminology standards.
Data Source Identification: Requires knowledge of functional business domain and scenarios; Categories of data and where it is held; Business data requirements; Database technologies and distributed datastores (e.g. SQL, NoSQL); Data Quality; Existing business systems and processes, including the key drivers and measures of success. To understand the priority order of requirements and service level agreements. Define and identify the most suitable sources for required data that is fit for purpose, referring to external sources as required. Perform initial data quality checks on the extracted data. Review the deliverables of junior associates and provides guidance on data source and quality.

Data Architecture: Requires knowledge of data ecosystem and integration blueprints including transactional database systems, data warehouse, business intelligence, and analytics systems; Data warehousing, data architecture, data profiling, data integration, ETL, and database design tools and techniques; Physical, Conceptual and Logical data modeling (relational and dimensional); Technological standards and best practices within modeling processes; Data Architecture standards, processes, and methodologies (for example, data manipulating processes, database technology generating processes); Cloud data warehouses, infrastructure, and services (for example, Redshift, Azure, BigQuery, Snowflake); Open-Source Big Data Technologies (for example, Hadoop, Kafka, NoSQL Databases). To diagnose the rationality and reliability of conceptual, logical, and physical layers. Select criteria used to support data processing operations, data flow, and the flow control system. Troubleshoot connections between information architecture, information systems, data architecture, and data delivery systems. Assist with data planning, sourcing, collection, and transformation. Test the effectiveness of the database before release for business use. Design data schemes, object models, and flow diagrams to structure, store, process and integrate data. Help maintain the integrity and security of the database. Provide architectural assessments, strategies, and roadmaps for+G6 data management. Develop proof-of-concept to validate new architectures and solutions. Examine and identifies database structural necessities by evaluating client operations, applications, and programming. Improve system performance by conducting tests, troubleshooting, and integrating new elements.

Data Modeling: Requires knowledge of cloud data strategy, data warehouse, data lake, and enterprise big data platforms; Data modeling techniques and tools (For example, Dimensional design and scalability), Entity Relationship diagrams, Erwin, etc; Query languages SQL / NoSQL; Data flows through the different systems; Tools supporting automated data loads; Artificial Intelligent - enabled metadata management tools and techniques. To assemble large, complex data across all data platforms (for example, relational, dimensional, NoSQL) and data tools. Build complex logical and conceptual models and provides guidance to team on physical data models. Identify and define the appropriate techniques for exposing data to other systems. Review and provide guidance and inputs on all data modeling activities to team members. Create and maintain critical data documentation and metadata that allows data to be understood and leveraged as a shared asset. Assist in defining data modeling standards and foundational best practices. Provide inputs to the architectural design to make best use of the available resources, given goals, and expected loads.

Understanding Business Context: Requires knowledge of industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. To evaluate proposed business cases for projects and initiatives. Translate business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives, and drives the execution of deliverables. Build and articulate the business case and return on investment and delivers work that has demonstrable value. Challenge business assumptions on topics related to one's domain expertise. Mentor the team members on new business insights and allied developments. Proactively engage in the external community to build Walmart's brand and learn more about industry practices.

Tech. Problem Formulation: Requires knowledge of analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. To analyze the business problem within one's discipline and questions assumptions to help the business identify the root cause. Identifies and recommends approach to resolve the business problem to create effective technology focused solutions. Set relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution. Quantify business impact.

Data Governance: Requires knowledge of data value chains; Data processes and practices; Regulatory and ethical requirements around data; Data modeling, storage, integration, and warehousing; Data value chains (identification, ingestion, processing, storage, analysis, and utilization); Data quality framework and metrics; Regulatory and ethical requirements around data privacy, security, storage, retention, and documentation; Business implications on data usage; Data Strategy; Enterprise regulatory and ethical policies and strategies. To establish, modify, and document data governance strategies and initiatives. Provide guidance to business stakeholders, peers, and junior associates on the implementation of data governance practices. Help business leaders understand and interpret company and regulatory policies around data. Determine data governance processes, practices, policies, and guidelines. Drive the successful adoption of organizational data utilization. Educate others on roles and accountability for data management. Actively participate in external communities to grow and develop deeper understanding of political and regulatory changes that may happen from a data perspective.

Data Strategy: Requires knowledge of understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability etc; Understanding of the methods and applications that unlock the monetary value of data assets. To understand, articulate, interpret, and apply principles of the defined strategy to complex business problems. Leverage experiences and learnings to inform and influence data strategy that typically spans one or more functions or domains.

Data Quality Management: Requires knowledge of data quality management techniques and standards; Business metadata definitions and content data definitions; Data profiling tools, data cleansing tools, data integration tools, and issues and event management tools; Understanding of user's data consumption, data needs, and business implications; Data modeling, storage, integration, and warehousing; Data quality framework and metrics; User access best practices; Enterprise data architecture, modeling and design, storage, integration, and warehousing; Enterprise data quality framework and metrics; Enterprise data strategy; Enterprise data quality strategy; Enterprise strategy to address regulatory and ethical requirements and policies around data privacy, security, storage, retention, and documentation. To develop and evangelize data quality awareness. Determine data quality strategy, metrics, and business rules for a business domain to ensure that data is fit for purpose. Set and evaluate business domain data quality service level strategy. Design and implement operational Data Quality Management (DQM) procedures. Monitor operational DQM procedures and performance. Lead data quality initiatives to deliver increased business performance and effectiveness. Determine user accessibility and removes or restricts user access as needed. Provide recommendations to leadership on needed updates or inputs into data governance policies, practices, and guidelines.

Provides overall direction by analyzing business objectives and customer needs; developing, communicating, building support for, and implementing business strategies, plans, and practices; analyzing costs and forecasts and incorporating them into business plans; determining and supporting resource requirements; evaluating operational processes; measuring outcomes to ensure desired results; identifying and capitalizing on improvement opportunities; promoting a customer environment; and demonstrating adaptability and sponsoring continuous learning.

Develops and implements strategies to attract and maintain a highly skilled and engaged workforce by diagnosing capability gaps; recruiting, selecting, and developing talent; supporting mentorship, workforce development, and succession planning; and leveraging the capabilities of new and existing talent.

Cultivates an environment where associates respect and adhere to company standards of integrity and ethics by integrating these values into all programs and practices; developing consequences for violations or non-compliance; and supporting the Open Door Policy.

Develops and leverages internal and external partnerships and networks to maximize the achievement of business goals by sponsoring and leading key community outreach and involvement initiatives; engaging key stakeholders in the development, execution, and evaluation of appropriate business plans and initiatives; and supporting associate efforts in these areas.

#LI-MF4

Live our Values

Culture Champion

• Models the Walmart values to foster our culture; holds oneself and others accountable; and supports Walmart's commitment to communities, social justice, corporate social responsibility, and sustainability; maintains and promotes the highest standards of integrity, ethics and compliance.

Servant Leadership

• Acts as an altruistic servant leader and is consistently humble, self-aware, honest, and transparent.

Embrace Change

Curiosity & Courage

• Demonstrates curiosity and a growth mindset; fosters an environment that supports learning, innovation, and intelligent risk-taking; and exhibits resilience in the face of setbacks.

Digital Transformation & Change

• Seeks and implements continuous improvements and encourages the team to leverage new digital tools and ways of working.

Deliver for the Customer

Customer Focus

• Delivers expected business results while putting the customer first and consistently applying an omni-merchant mindset and the EDLP and EDLC business models to all plans.

Strategic Thinking

• Adopts a holistic perspective that considers data, analytics, customer insights, and different parts of the business when making plans and shaping the team's strategy.

Focus on our Associates

Diversity, Equity & Inclusion

• Identifies, attracts, and retains diverse and inclusive team members; builds a high-performing team; embraces diversity in all its forms; and actively supports diversity goal programs.

Collaboration & Influence

• Builds strong and trusting relationships with team members and business partners; works collaboratively and cross-functionally to achieve objectives; and communicates with energy and positivity to motivate, influence, and inspire commitment and action.

Talent Management

• Creates a discipline and focus around developing talent, promotes an environment allowing everyone to bring their best selves to work, empowers associates and partners to act in the best interest of the customer and company, and regularly recognizes others' contributions and accomplishments.

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelor's degree in Computer Science or related field and 6 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field. Option 2: 8 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field. Option 3: Master's degree in Computer Science and 4 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field.
2 years' supervisory experience.

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data architecture/software architecture/data modeling, Master's degree in Computer Science or related field and 6 years' experience in software engineering, Relevant industry experience (for example, retail, supply chain, eCommerce, healthcare, etc.), Solution Architecture, Supervisory

Primary Location...
2608 Se J St, Bentonville, AR , United States of America

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