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Advanced Data Engineer

Kroger Family of Companies - Blue Ash, OH

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Job Description

This role leads the design and operation of data pipelines that accurately reflect the operational Customer Graph. The engineer will oversee the migration to Databricks in support of the new Customer Platform Analytics, while ensuring the continued reliability of existing Netezza and Neo4j systems through rigorous monitoring and timely issue resolution. Accountable for leading activities that create deliverables to guide the direction, development, and delivery of technological responses to targeted business outcomes. Provide facilitation, analysis and design tasks required for the development of an enterprise's data and information architecture, focusing on data as an asset for the enterprise. Develop reusable standards, design patterns, guidelines, and configurations to evolve the technical infrastructure related to data and information across the enterprise, including direct collaboration with 84.51. Demonstrate the company's core values of respect, honesty, integrity, diversity, inclusion and safety. RESPONSIBILITIES - Participate in the development and communication of data strategy and roadmaps across the technology organization to support project portfolio and business strategy - Participate in, and drive, the development and communication of enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses - Provide technical leadership to ensure clarity between ongoing projects, including direct collaboration with 84.51 - Drive digital innovation by leveraging innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms - Define high-level migration plans to address the gaps between the current and future state - Present opportunities with cost/benefit analysis to leadership to shape sound architectural decisions - Lead the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement - Mentor team members in data principles, patterns, processes and practices - Promote the reuse of data assets, including the management of the data catalog for reference - Draft and review architectural diagrams, interface specifications and other design documents - Must be able to perform the essential job functions of this position with or without reasonable accommodation QUALIFICATIONS Minimum Bachelors Degree computer science, or software engineering, or related field Any experience defining evolutionary data solutions and underlying technologies 7+ years successful and applicable experience taking a lead role in building complex data solutions that have been successfully delivered to customers 7+ years proven track record of designing and delivering large scale, high quality operational or analytical data systems 7+ years successful and applicable hands on experience in the data development and principles including endtoend design patterns Demonstrated written and oral communication skills Knowledge in a minimum of two of the following technical disciplines: data warehousing, data management, analytics development, data science, application programming interfaces (APIs), data integration, cloud, servers and storage, and database management Strong knowledge of industry trends and industry competition Basic understanding of network and data security architecture Desired Any experience building solutions using elastic architectures (preferably Microsoft Azure and Google Cloud Platform) Any experience with data science solutions or platforms Any experience with operational data science, machine learning or artificial intelligence solutions Any experience with a variety of SQL, NoSQL and Big Data Platforms Handson experience with Databricksbeyond basic usage (performance tuning, cost optimization, cluster management) Prior experience leading or participating in largescale data platform migrations Strong background in data quality frameworks, reconciliation, and anomaly detection

Created: 2026-02-27

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