Senior, Data Engineer

About the role

Everyone has data, but the sheer volume of data at Walmart can be limitless. In the Data Engineering team, we help Walmart manage this data by building pipelines and data lakes to prepare big data for analysis and unlocking actionable insights in real-time. We also use cross-departmental data and machine learning to build a holistic view of true profitability, saving millions of dollars across item categories and geographies while assisting our leadership in making better decisions faster. What you'll do: Data Strategy: Understands, articulates and applies principles of the defined strategy to routine business problems that involve a single function. Data Transformation and Integration: Extracts 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 analytics trends. Data Source Identification: 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. Data Modelling: Analyses 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. Analyses data-related system integration challenges and proposes appropriate solutions. Code Development and Testing: Writes 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 validatethe 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. Problem Formulation: Translates business problems within one's discipline to data related or mathematical solutions. Identifies what methods (for example, analytics, big data analytics, automation) would provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem. Applied Business Acumen: 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. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Recommends new processes and ways of working. Data Governance: Establishes, modifies, and documents 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. Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others. Supporting and aligning efforts to meet customer and business needs and building commitment for perspectives and rationales. What you'll bring: 7-10 years of Data engineering experience 2 - 3 Years of Experience in GCP/Azure cloud platforms Demonstrates up-to-date expertise in Data Engineering, complex data pipeline development Architect, Design, develop, implement and tune distributed data processing pipelines that process large volume of data; focusing on scalability, low -latency, and fault-tolerance in every system built. Proven experience in data modeling and design, with a strong understanding of data architecture principles and best practices. Exposure to Data Governance ( Data Quality, Metadata Management, Security, etc.) Expertise in using tools such as JUnit, TestNG, or PyUnit to write and execute unit tests, and experience with CI/CD pipelines to automate testing processes. Experience with Java, Scala and/or Python to write data pipelines and data processing layers Demonstrates experti

Additional Information

Position Summary... What you'll do... Come join our Merchandising Data Engineering Team @Walmart ,where you'll play a key role in managing and delivering high-quality, consistent merchandising data at scale. This role offers the opportunity to work with complex datasets that power analytical systems, driving key business decisions.

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