2 months ago
Base Salary
$110k - $209k/yr
Responsibilities
- Design, develop, implement, and oversee legacy ETL and cloud-native data ingestion frameworks and end-to-end data pipelines.
- Assess information needs and data flows to engineer scalable, reliable, and cost-effective data solutions.
- Architect Supply Chain analytical solutions using Apache Iceberg and Medallion Architecture while ensuring data quality, lineage, and accessibility.
- Build, optimize, and maintain AWS Redshift data warehouse solutions and data products.
- Define and implement Data Product-centric architecture and data mesh principles, including standards for ownership, discoverability, and interoperability.
- Partner with Supply Chain stakeholders to model data flows from SAP and planning systems and create governed, analytics-ready data products.
- Lead and consult with the technical data engineering team, supervise team members as needed, and remain accountable for delivery and performance.
- Establish and apply data governance, cataloging, metadata management, lineage, and data quality practices.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field plus 7+ years of data architecture and data engineering experience; alternatively, a master’s degree plus 6 years or a PhD plus 2 years.
- Deep hands-on expertise with AWS Glue, Amazon S3, AWS EMR, and related ingestion and transformation technologies such as Informatica.
- Hands-on experience with Apache Iceberg or similar lakehouse technologies.
- Proficiency with AWS Redshift or similar modern data warehousing platforms.
- Experience designing and implementing Medallion Architecture and Data Product frameworks, with familiarity with data mesh principles.
- Familiarity with Supply Chain ERP systems, specifically SAP, and core Supply Chain data flows and domains.
- Familiarity with Blue Yonder planning domains, data models, and integration patterns.
- Strong ETL, SQL, Python, and Apache Spark/PySpark programming and query skills for large-scale data transformation and pipeline development.
- Knowledge of data governance, Alation or AWS Glue Data Catalog, metadata management, data lineage, and data quality practices.
- Ability to analyze complex requirements, evaluate technical options, deliver scalable solutions, work autonomously, and engage senior stakeholders.
- Knowledge of reporting tools such as Power BI is preferred.
Benefits
- Comprehensive paid time off, including vacation, holidays, and sick leave.
- Medical, dental, and vision insurance and a 401(k) for eligible employees.
- Eligibility to participate in long-term incentive programs.
- The role includes approximately 5% travel.
- The listed annual base pay range is USD 109,500–208,500; compensation may vary by location and other factors.
Tech Stack
Categories
Data Engineering