SENIOR, DATA ENGINEER

• 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 translate/ co-own business problems within ones discipline to data related or mathematical solutions
• Identifies appropriate methods/tools to be leveraged to provide a solution for the problem
• Shares use cases and gives examples to demonstrate how the method would solve the business problem
• 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 provide recommendations to business stakeholders to solve complex business issues
• Develops business cases s for projects with a projected return on investment or cost savings
• Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact
• Serves as an interpreter and conduit to connect business needs with tangible solutions and results
• Identify and recommend relevant business insights pertaining to their area of work
• 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 (eg SQL, NoSQL); Data Quality; Existing business systems and processes, including the key drivers and measures of success
• To support the understanding of the priority order of requirements and service level agreements
• Helps identify the most suitable source for data that is fit for purpose
• Performs initial data quality checks on extracted data
• Data Transformation and Integration Requires knowledge of: Internal and external data sources including how they are collected, where and how they are stored, and interrelationships, both within and external to the organization;
• Techniques like ETL batch processing, streaming ingestion, scrapers, API and crawlers; Data warehousing service for structured and semi-structured data, or to MPP databases such as Snowflake, Microsoft Azure, Presto or Google BigQuery; Pre-processing techniques such as transformation, integration, normalization, feature extraction, to identify and apply appropriate methods; Techniques such as decision trees, advanced regression techniques such as LASSO methods, random forests etc; Cloud and big data environments like EDO2 systems
• To extract data from identified databases
• Creates data pipelines and transform data to a structure that is relevant to the problem by selecting appropriate techniques
• Develops knowledge of current data science and analytics trends
• 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 analyze complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models
• Develops the Logical Data Model and Physical Data Models including data warehouse and data mart designs
• Defines relational tables, primary and foreign keys, and stored procedures to create a data model structure
• Evaluates existing data models and physical databases for variances and discrepancies
• Develops efficient data flows
• Analyzes data-related system integration challenges and proposes appropriate solut Code Development and Testing Requires knowledge of: Coding languages like SQL, Java, C++, Python and others; Testing methods such as static, dynamic, software composition analysis, manual penetration testing and others; Business, domain understanding
• To write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements
• Creates test cases to review and validate the proposed solution design
• Creates proofs of concept
• Tests the code using the appropriate testing approach
• Deploys software to production servers
• Contributes code documentation, maintains playbooks, and provides timely progress updates
• 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 projects and recommendations
• Implements data governance practices in partnership with business stakeholders and peers
• Interprets company and regulatory policies on data
• Educates others on data governance processes, practices, policies, and guidelines
• Provides recommendations on needed updates or inputs into data governance policies, practices, or guidelines
• 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, and apply principles of the defined strategy to routine business problems that involve a single function

Leadership Expectations

Respect for the Individual: Demonstrates and encourages respect for all; builds a high-performing, diverse team; seeks, and embraces differences in people, cultures, ideas and experiences; creates a workplace and equitable experiences where associates feel seen, supported and connected through culture of belonging so associates thrive and perform; drives a positive associate and customer/member experience for all; identifies, attracts, and retains the best, diverse team members.

Respect for the Individual: Creates a discipline and focus around developing talent, through feedback, coaching, mentoring, and developmental opportunities; 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/member and company; and regularly recognizes others contributions and accomplishments.

Respect for the Individual: Builds strong and trusting relationships with team members and business partners; works collaboratively and cross-functionally to achieve objectives; and communicates and listens attentively, with energy and positivity to motivate, influence, and inspire commitment and action.

Acts with Integrity: Maintains and promotes the highest standards of integrity, ethics and compliance; models the Walmart values and leads by example to foster our culture; supports Walmart s goal of becoming a regenerative company by making a positive impact for associates, customers, members, and the world around us.

Acts with Integrity: Follows the law, our code of conduct and company policies, and sets expectations for others to do the same; promotes an environment where associates feel comfortable sharing concerns and reinforces our culture of non-retaliation; listens to concerns raised by associates. takes action and encourages others to do the same; holds self and others accountable for achieving results in a way that is consistent with our values.

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

Service to the Customer/Member: Delivers expected business results while putting the customer/member first and consistently applying an omni-merchant mindset and acts with an Every Day Low Cost mindset to drive value and Every Day Low Prices for customers/members.

Service to the Customer/Member: Adopts a holistic perspective that considers data, analytics, customer/member insights, and different parts of the business when making plans and shaping the team s strategy.

Strive for Excellence: Consistently raises the bar and seeks to improve; demonstrates curiosity and a growth mindset; seeks feedback, asks thoughtful questions, fosters an environment that supports learning, innovation, and learning from mistakes, and intelligent risk-taking; and exhibits resilience in the face of setbacks.

Strive for Excellence: Seeks and implements continuous improvements and encourages the team to leverage new digital tools and ways of working.