Senior, Data Engineer

Position Summary...

What you'll do...

Be a part of our International Data Organization within Walmart's Global Data Foundation, driving large-scale International Supply Chain data initiatives and enabling consistent, high-quality data to power critical business use cases across global markets. About Team:

International Data Organization, where we build and manage enterprise-scale data lakes that power all international markets. Our platform enables both in-market teams and home office associates to make smarter, faster decisions using accurate, up-to-date, and easily accessible data.

As part of our Data Engineering team, you will contribute to high-impact Single Source of Truth (SSOT) data products such as eComm Fulfillment 360, Store Fulfillment 360, and Omni Transaction 360. We design and deliver scalable data pipelines that drive key performance indicators across critical business domains, including Supply Chain, Fulfillment, and Finance.

This is a unique opportunity to work at the scale of a global retail leader, leveraging advanced data integration, modeling, and strategy to influence business outcomes and drive meaningful impact worldwide.

What you'll do:

* Design, build, and enhance high-performance, reusable frameworks for data pipelines.

* Develop and deploy cutting-edge solutions at scale, impacting millions of customers worldwide and driving value from data at enterprise scale.

* Support International Supply Chain data applications while ensuring adherence to data quality and governance standards.

* Collaborate with Walmart engineering teams across geographies to leverage expertise and contribute to the technical community.

* Ensure data ingested and processed is accurate and of high quality by implementing robust data quality checks, validation, and data cleansing processes.

* Analyze and translate business requirements into strategies, initiatives, and projects, aligning with business objectives and driving execution of deliverables.

* Define and identify the most suitable data sources that are fit for purpose, incorporating external data sources when required.

* Build scalable infrastructure for optimal transformation and integration across a wide variety of data sources using modern data integration technologies.

* Utilize modern tools, techniques, and architectures to automate common, repeatable, and complex data preparation and integration tasks.

* Collaborate effectively with team members to solve complex business problems and deliver impactful solutions.

* Leverage AI-assisted development tools (e.g., code generation, automated debugging, and optimization tools) to accelerate data pipeline development and improve engineering productivity.

* Utilize AI-driven data profiling and anomaly detection techniques to proactively identify data quality issues and improve data reliability.

* Implement intelligent automation using AI/ML techniques to optimize data pipeline performance, resource utilization, and execution efficiency.

* Apply AI-based approaches for metadata management, schema evolution, and data lineage tracking to enhance data discoverability and governance.

* Use generative AI tools to accelerate documentation, code standardization, and knowledge sharing across data engineering teams.

* Integrate AI-powered monitoring and observability solutions to detect pipeline failures, predict issues, and enable proactive remediation.

What you'll bring:

* Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.

* 5+ years of hands-on experience building and delivering scalable data pipelines and big data solutions.

* Strong expertise in managing and processing large-scale datasets (terabyte scale and beyond).

* Proficiency in big data technologies such as Hadoop, Apache Spark, Apache Hive, and cloud platforms (GCP preferred, Azure or equivalent), with a focus on building optimized, fault-tolerant, and SLA-driven batch pipelines.

* Strong programming skills in languages such as Scala and Python, with a proven ability to write clean, efficient, and production-ready code.

* Experience designing and orchestrating idempotent workflows using tools like Apache Airflow or similar orchestration frameworks.

* Advanced SQL skills to analyze, profile, and optimize large datasets, preferably using Big Query, Spark SQL, or similar platforms.

* Hands-on experience working with distributed messaging systems such as Kafka or equivalent streaming platforms.

* Strong data modeling expertise to design scalable and flexible schemas that support evolving data sources and enable efficient data integration.

* Ability to partner with business and technical stakeholders to gather requirements and translate them into scalable data solutions and pipelines.

* Strong analytical and problem-solving skills, with the ability to identify, troubleshoot, and resolve complex data engineering challenges.

* Ability to operate in a fast-paced environment, delivering high-quality outcomes with minimal ramp-up time.

* Excellent…