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• Lead, mentor, and manage a high-performing data engineering team, ensuring technical and career growth
• Define and drive architecture of enterprise-scale Health and Wellness data lake
• Design and maintain scalable ETL/ELT pipelines for batch and real-time data processing
• Oversee development of robust enterprise data warehouse systems
• Collaborate with product managers, data scientists, and business stakeholders to build data products
• Deliver end-to-end scalable data and analytics solutions for business use cases
• Establish standards for data quality, governance, integrity, and reliability
• Implement data security and compliance frameworks including healthcare regulations like HIPAA
• Drive innovation and best practices in data engineering and platform development
What started small, with a single discount store and the simple idea of selling more for less, has grown over the last 50 years into the largest retailer in the world. Each week, nearly 265 million customers and members visit our more than 11,200 stores under 55 banners in 27 countries and eCommerce websites in 10 countries. With fiscal year 2018 revenue of $500.3 billion, Walmart employs over 2.2 million associates worldwide. Walmart continues to be a leader in sustainability, corporate philanthropy and employment opportunity. It’s all part of our unwavering commitment to creating opportunities and bringing value to customers and communities around the world
Job ID: 146591379
Skills:
data engineering , Kafka, Azure Data Factory, Azure Synapse Analytics, Spark, Databricks, Dax, Python, Azure DevOps, Purview, R, Microsoft Fabric
Skills:
Python, Kafka, MongoDB, OLAP/Data Pipelines, Apache Presto
Skills:
snowflake , Databricks, Microservices, Automated Testing, Reactjs, Azure, Git, Oracle Pl Sql, CI CD integration, distributed processing frameworks, frontend technologies, data pipelines, data Lakehouse, containerized applications, AI tools
Skills:
snowflake , Algorithms, Databricks, Microservices, Automated Testing, Reactjs, Accessibility, Agile Methodologies, Coding Standards, Azure, Git, Oracle Pl Sql, data structures, CI CD integration, distributed processing frameworks, data pipelines, frontend architecture design patterns, data Lakehouse, modern frontend technologies, containerized applications, unit testing strategies, AI tools, UI performance optimization
Skills:
Power Bi, Apache Spark, Databricks, Azure, Python, Sql, SODA or equivalent data quality observability tools, CI CD for data pipelines, Delta Lake, Atlan or similar data catalog and metadata platforms
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