Senior Engineer, Technology II (Data Engineering & Architecture)

- Familiarity with Blue Yonder (formerly JDA) planning domain covering demand planning, supply planning etc. including understanding of the underlying data models and integration patterns with enterprise data platforms. - Strong programming and query skills in ETL, SQL, Python, and Apache Spark/PySpark for large-scale data transformation, processing, and pipeline development. - Solid knowledge of data governance frameworks, data cataloging using Alation or AWS Glue Data Catalog, metadata management, data lineage, and data quality practices; experience implementing enterprise-wide data governance policies and controls.

Job Description The Sr. Data Engineer & Solution Architect serves as the principal designer for Operations Data organization, with a focus on cloud-native data lakehouse architecture, advanced data engineering, and Supply Chain data domains. This role is responsible for conceiving, designing, and implementing scalable, high-performance data solutions leveraging modern AWS Database & Analytics services, Apache Iceberg open table format, AWS Redshift, and Medallion Architecture principles. The Sr. Data Engineer & Solution Architect will drive Data Product-centric thinking and data mesh principles for the organization, partnering closely with Supply Chain functional and business stakeholders to deliver trusted, governed, and actionable data and dashboards across from Supply Chain domains. This role requires a deep combination of hands-on technical expertise, solution architecture, and the ability to communicate complex data strategies to both technical teams and cross functional stakeholders. Responsibilities:

Responsibilities: - Design, develop, implement and oversee legacy ETL and cloud-native data ingestion frameworks and end-to-end data pipelines leveraging AWS services including AWS Glue, Amazon S3, AWS EMR, AWS Lambda, and other ingestion / ETL technologies like Informatica; assess information needs and data flows to engineer scalable, reliable, and cost-effective solutions. - Solution architect data need for the Operations Supply Chain analytical use cases using Apache Iceberg open table format, implementing Medallion Architecture to ensuring data quality, lineage, and accessibility.

- Solution architect data need for the Operations Supply Chain analytical use cases using Apache Iceberg open table format, implementing Medallion Architecture to ensuring data quality, lineage, and accessibility. - Build, optimize, and maintain AWS Redshift data warehouse solutions for Supply Chain analytical use cases, including the design of data products leveraging AWS Redshift aligned to enterprise analytics consumption patterns. - Define, promote, and implement Data Product-centric architecture and data mesh principles from business domains; establish standards for data product design, ownership, discoverability, and interoperability to enable all analytical Dashboards and AI use cases.

- Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, or a related field with 7+ years of experience in data architecture and data engineering; Master's Degree with 6 years' experience; or PhD with 2 years of experience. - Deep, hands-on expertise with modern AWS Database & Analytics services including AWS Glue, Amazon S3, AWS EMR and related ingestion and transformation technologies like Informatica. - Demonstrated hands-on experience with Apache Iceberg open table format or similar technologies for lakehouse architecture.

- Demonstrated hands-on experience with Apache Iceberg open table format or similar technologies for lakehouse architecture. - Proficiency with AWS Redshift for enterprise data warehousing or similar Modern data warehousing platforms. - Proven experience designing and implementing Medallion Architecture (Bronze/Silver/Gold layers) and Data Product frameworks; familiarity with data mesh principles including domain ownership, data product thinking.

- Strong programming and query skills in ETL, SQL, Python, and Apache Spark/PySpark for large-scale data transformation, processing, and pipeline development. - Solid knowledge of data governance frameworks, data cataloging using Alation or AWS Glue Data Catalog, metadata management, data lineage, and data quality practices; experience implementing enterprise-wide data governance policies and controls. - Demonstrated ability to analyze complex business requirements, evaluate technical options, and deliver efficient, scalable, and cost-effective data solutions; proven experience operating with a high degree of autonomy in enterprise or regulated IT environments, balancing technical depth, architecture leadership, and senior stakeholder engagement.

- Design, develop, implement and oversee legacy ETL and cloud-native data ingestion frameworks and end-to-end data pipelines leveraging AWS services including AWS Glue, Amazon S3, AWS EMR, AWS Lambda, and other ingestion / ETL technologies like Informatica; assess information needs and data flows to engineer scalable, reliable, and cost-effective solutions. - Solution architect data need for the Operations Supply Chain analytical use cases using Apache Iceberg open table format, implementing Medallion Architecture to ensuring data quality, lineage, and accessibility. - Build, optimize, and maintain AWS Redshift data warehouse solutions for Supply Chain analytical use cases, including the design of data products leveraging AWS Redshift aligned to enterprise analytics consumption patterns.

- Deep, hands-on expertise with modern AWS Database & Analytics services including AWS Glue, Amazon S3, AWS EMR and related ingestion and transformation technologies like Informatica. - Demonstrated hands-on experience with Apache Iceberg open table format or similar technologies for lakehouse architecture. - Proficiency with AWS Redshift for enterprise data warehousing or similar Modern data warehousing platforms.

- Define, promote, and implement Data Product-centric architecture and data mesh principles from business domains; establish standards for data product design, ownership, discoverability, and interoperability to enable all analytical Dashboards and AI use cases. - Partner with Supply Chain BTS (IT) functional and business stakeholders to understand and model critical data flows across from SAP and planning systems processes; translate complex ERP data structures into governed, analytics-ready data products within the lakehouse platform. - Lead consultant technical data engineering team responsible for building the solutions; supervise team members as needed, remain accountable for team delivery and performance, and cultivate a culture of engineering excellence and continuous improvement.

- Proven experience designing and implementing Medallion Architecture (Bronze/Silver/Gold layers) and Data Product frameworks; familiarity with data mesh principles including domain ownership, data product thinking. - Familiarity with Supply Chain ERP systems, specifically SAP, and working knowledge of core Supply Chain data flows and data domains. - Familiarity with Blue Yonder (formerly JDA) planning domain covering demand planning, supply planning etc. including understanding of the underlying data models and integration patterns with enterprise data platforms.

Preferred: - Knowledge of reporting tools such as PowerBI etc. is a plus for the role. Additional Information