
Manager, Data Engineering
- Data Modeling
- SQL
- NoSQL
- AI
- UML
- Adobe
- MS Project
- Azure DevOps
- Jira
- Confluence
- Smartsheet
- JSON
- Selenium
- Load Testing
- JMeter
- Agile
- Scrum
- Google Analytics
What you'll do...
Position: Manager, Data EngineeringÂ
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Job Location: 811 Excellence Dr, Bentonville, AR 72716Â
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Duties: Demonstrates up-to-date expertise and apply this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales. Performs analytics/big data analytics/automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. Translates/co-owns business problems within 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. Provides recommendations to business stakeholders to solve complex business issues. Develops business cases 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 conducts to connect business needs with tangible solutions and results. Identifies and recommends relevant business insights pertaining to their area of work. Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities. Supports 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. Extracts data from identified databases. Creates data pipelines and transforms data to a structure that is relevant to the problem by selecting appropriate techniques. Develops knowledge of current data science and analytics trends. Performs data modeling: 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 Intelligence-enabled metadata management tools and techniques. Analyzes complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Develops 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 solutions. Creates training documentation and trains end-users on data modeling. Â
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Minimum education and experience required: Bachelor's degree or the equivalent in Computer Science, Business Administration, Engineering, or related field plus 3 years of experience in software engineering or a related field; OR Master’s degree or the equivalent in Computer Science, Business Administration, Engineering, or related field plus 1 year of experience in software engineering or a related field.Â
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Skills Required: Must have experience with: Gathering business requirements from key stakeholders by using techniques like prototyping, workshops, focus groups to determine and carry out necessary processes and practices, recognizing and improvements opportunities; Translating business requirements into technical documentation by creating user stories, Workflows, UML (Unified Modeling Language) diagrams, BRD - Business requirements document based on the business needs and the Adobe commerce platform capabilities; Helping stakeholders in understanding capabilities of the Adobe Commerce platform and making necessary updates to their eCommerce application configurations related product data setup; Preparing a project plan by using tools like MS-Project Azure DevOps, JIRA/Confluence, Smartsheet; Creating a project charter, budget tracker by using Microsoft Suite; Defining data transformation and data modeling strategies by retrieving existing data through queries by using SQL and creating Entity Relation Diagrams; Testing APIs responses implemented in REST, JSON and document required changes; Implementing testing strategy, plans and test cases using Selenium; Performing Load Testing on an ecommerce platform/application along with Quality engineering by using JMeter; Implementing Agile best practices for the team using Scrum framework and SAFe; Preparing various reports in JIRA/Confluence, AzureDev Ops tool; Reviewing data analytics to gain insight into customer behavior, site traffic and performance by using tools like Google Analytics, Hot Jar, Full Story and identify improvement opportunities. Employer will accept any amount of experience with the required skills.Â
 Rate of pay: $110,000.00 - 220,000.00/yearÂ
Wal-Mart is an Equal Opportunity Employer.Â
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Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.Manager, Data Engineering · Walmart Inc.