Staff, Data Engineer

Walmart•Bentonville, AR

20h

About The Position

What you'll do... Position: Staff, Data Engineer Job Location: 2608 SE J St, Bentonville, AR 72716 Duties: Tech. Problem Formulation: Translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identify appropriate methods/tools to be leveraged to provide solution for problem. Share use cases and give examples to demonstrate how method would solve business problem. Understanding Business Context: Provide recommendations to business stakeholders to solve complex business issues. Develop business cases for projects with projected return on investment or cost savings. Translate business requirements into projects, activities, and tasks and align to overall business strategy and develop domain specific artifact. Serve as 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: Understand priority order of requirements and service level agreements. Define and identify most suitable sources for required data that is fit for purpose, referring to external sources as required. Perform initial data quality checks on extracted data. Review deliverables of junior associates and provide guidance on data source and quality. Data Transformation and Integration: Build infrastructure required for optimal transformation and integration from wide variety of data sources using appropriate data integration technologies. Use modern tools, techniques, and architectures to partially or completely automate most-common, repeatable and tedious data preparation and integration tasks. Deploy pipelines using scheduling and orchestration frameworks. Evaluate impacts of data issues and risks at early stage. Identify needs and create methods to fuse and reshape complex, multi-source data and make it usable for modeling. Update knowledge of current and emerging big data analytics and data science trends and techniques. Data Modeling: Assemble large, complex data across all data platforms and data tools. Build complex logical and conceptual models and provide guidance to team on physical data models. Identify and define appropriate techniques for exposing data to other systems. Review and provide guidance and input 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 shared asset. Assist in defining data modeling standards and foundational best practices. Provide inputs to architectural design to make best use of available resources, given goals, and expected loads. Code Development and Testing: Review solution and application design to ensure it meets business, technical, and data requirements. Identify language and libraries to use in development process. Map test cases to business and functional requirements. Create proof of concepts. Review and troubleshoot code in line with final designs. Identify and recommend appropriate testing methodology. Identify environment(s) for deployment. Identify and recommend modifications of application based on different environment requirements. Identify modifications needed for scalability and drive change. Monitor applications in production and lead development of patches where required. Review and ensure all code documentation is complete and updated periodically. Data Governance: Establish, modify, and document data governance projects and recommendations. Implement data governance practices in partnership with business stakeholders and peers. Interpret company and regulatory policies on data. Educate others on data governance processes, practices, policies, and guidelines. Provide recommendations on needed updates or inputs into data governance policies, practices, or guidelines. Data Strategy: Understand, articulate, interpret, and apply principles of defined strategy to unique, moderately complex business problems.

Requirements

Master's degree or the equivalent in Computer Science, Information Technology, Engineering, or related field and 2 years of experience in software engineering or related experience; OR Bachelor’s degree or the equivalent in Computer Science, Information Technology, Engineering, or related field and 4 years of experience in software engineering or related experience.
Must have experience with: Designing, development and testing Relational Database Management Systems (MySQL, Microsoft SQL Server, Postgres); Working in fast paced environment following Agile methodologies; Data warehousing concepts, methodologies, and frameworks using current (SparkSQL, Hadoop, Kafka, Hive) distributed technologies; Designing and developing analytical dashboards using Business Intelligence Reporting Tools (Tableau, PowerBI, Looker); Coding in Object-Oriented programming languages (Java, Python, Scala); Coding in scripting language (Python, Shell scripts, Ruby, Perl); Software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source control management, build processes, testing, and operations (Git, Jenkins); Identifying business use cases and transform business problems to scalable analytical solutions; Using IDE tools (VSCode, IntelliJ); Identifying, debugging issues corresponding to the business domain and designing solutions; and Datastructures and algorithms.
Employer will accept any amount of graduate coursework, graduate research experience or experience with the required skills.

Responsibilities

Translate/ co-own business problems within one's discipline to data related or mathematical solutions.
Identify appropriate methods/tools to be leveraged to provide solution for problem.
Share use cases and give examples to demonstrate how method would solve business problem.
Provide recommendations to business stakeholders to solve complex business issues.
Develop business cases for projects with projected return on investment or cost savings.
Translate business requirements into projects, activities, and tasks and align to overall business strategy and develop domain specific artifact.
Serve as interpreter and conduit to connect business needs with tangible solutions and results.
Identify and recommend relevant business insights pertaining to their area of work.
Understand priority order of requirements and service level agreements.
Define and identify most suitable sources for required data that is fit for purpose, referring to external sources as required.
Perform initial data quality checks on extracted data.
Review deliverables of junior associates and provide guidance on data source and quality.
Build infrastructure required for optimal transformation and integration from wide variety of data sources using appropriate data integration technologies.
Use modern tools, techniques, and architectures to partially or completely automate most-common, repeatable and tedious data preparation and integration tasks.
Deploy pipelines using scheduling and orchestration frameworks.
Evaluate impacts of data issues and risks at early stage.
Identify needs and create methods to fuse and reshape complex, multi-source data and make it usable for modeling.
Update knowledge of current and emerging big data analytics and data science trends and techniques.
Assemble large, complex data across all data platforms and data tools.
Build complex logical and conceptual models and provide guidance to team on physical data models.
Identify and define appropriate techniques for exposing data to other systems.
Review and provide guidance and input 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 shared asset.
Assist in defining data modeling standards and foundational best practices.
Provide inputs to architectural design to make best use of available resources, given goals, and expected loads.
Review solution and application design to ensure it meets business, technical, and data requirements.
Identify language and libraries to use in development process.
Map test cases to business and functional requirements.
Create proof of concepts.
Review and troubleshoot code in line with final designs.
Identify and recommend appropriate testing methodology.
Identify environment(s) for deployment.
Identify and recommend modifications of application based on different environment requirements.
Identify modifications needed for scalability and drive change.
Monitor applications in production and lead development of patches where required.
Review and ensure all code documentation is complete and updated periodically.
Establish, modify, and document data governance projects and recommendations.
Implement data governance practices in partnership with business stakeholders and peers.
Interpret company and regulatory policies on data.
Educate others on data governance processes, practices, policies, and guidelines.
Provide recommendations on needed updates or inputs into data governance policies, practices, or guidelines.
Understand, articulate, interpret, and apply principles of defined strategy to unique, moderately complex business problems.