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Guide the team towards successful project delivery. Provide technical leadership and key decision making. Work with and mentor individual team members to meet professional goals. Continuous effort to automate and...
Design, build, test and deploy cutting edge solutions at scale, impacting millions of customers worldwide drive value from data. Interact with Sam's Club engineering teams across geographies to leverage expertise...
Leads one or more project teams of other data engineers for all stages of design and development for complex, secure and performant data solutions and models, including design, analysis, coding,...
Lead moderately complex initiatives within Technology and contribute to large scale data processing framework initiatives related to enterprise strategy deliverables. Build and maintain optimized and highly available data pipelines that...
Lead complex initiatives with broad impact and act as key participant in large scale software planning for the Technology area. Design, develop, and run tooling to discover problems in data...
Participate in data warehouses across multiple databases and identify opportunity for developing table schemas within the Technology and Date area. Review and analyze basic data management business, operational, or technical...
Proficient in SQL. Proficient in Spark or Python. Experience with MPP databases preferred. 6+ years of experience in data engineering and ETL pipeline development. 3+ years of Spark development. 6+...
Guide the team towards successful project delivery. Provide technical leadership and key decision making. Work with and mentor individual team members to meet professional goals. Continuous effort to automate and...
Data Engineers are responsible for designing, building, and maintaining the infrastructure and systems that support data management and analysis. They work closely with data scientists, data analysts and other stakeholders to ensure that data is properly collected, stored, and processed to meet the needs of the organization.
Data Engineers are well-versed in a variety of programming languages and technologies, including SQL, Python, and Java, as well as big data technologies like Hadoop and Spark. They have experience in data warehousing, data modeling, and data integration. They also have experience with cloud-based data storage and processing solutions like AWS Redshift and Google BigQuery.