Data Engineer, Integrated Planning Analytics and Insights
Architect, design, implement, enhance, and maintain highly scalable, available, secure, and elastic cloud-ready data solutions using cutting-edge technologies to support our predictive and prescriptive analytics needs. Be an expert in our data domains, act as a trusted partner and advisor to solutions architects and data scientists and become a crucial part of the analytics solution lifecycle – from prototype to production and operations of our data science and advanced analytics solutions in areas such as promotions, supply and demand planning, item/menu level analytics, supply chain simulations, and optimization, competitive benchmarking, and root cause analysis. Continuously improve and advance our data solutions.
responsibilities :
Responsible for working with the data management, data science, decision science, and technology teams to address supply chain data needs in demand and supply planning, replenishment, pricing, and optimization
Develops/refines the data requirements, designs/develops data deliverables, and optimizes data pipelines in non-production and production environments
Designs, builds, and manages/monitors data pipelines for data structures encompassing data transformation, data models, schemas, metadata, and workload management. The ability to work with both IT and business
Integrates analytics and data science output into business processes and workflows
Builds and optimizes data pipelines, pipeline architectures, and integrated datasets. These should include ETL/ELT, data replication/CI-CD, API design, and access
Works with and optimizes existing ETL processes and data integration and preparation flows and help move them to production
Works with popular data discovery, analytics, and BI and AI tools in semantic-layer data discovery
Adepts in agile methodologies and capable of applying DevOps and DataOps principles to data pipelines to improve communication, integration, reuse, and automation of data flows between data managers and data consumers across the organization
Implements Agentic AI capability to drive efficiency and opportunity
requirements-expected :
Bachelor’s degree in computer science, data management, information systems, information science or a related field; advanced degree in computer science, data management, information systems, information science or a related field preferred.
3+ years in data engineering building production data pipelines (batch and/or streaming) with Spark on cloud.
