Senior Engineer, Technology II (Data Engineering & Architecture)
AbbVie
August 30, 2026
Remote friendly (North Chicago, IL)
United States
$109,500 - $208,500 USD yearly
IT
Responsibilities:
- Design, develop, implement, and oversee legacy ETL and cloud-native data ingestion frameworks and end-to-end data pipelines using AWS (AWS Glue, Amazon S3, AWS EMR, AWS Lambda) and ingestion/ETL tools like Informatica; assess data needs and flows to build scalable, reliable, cost-effective solutions.
- Architect Operations Supply Chain analytical use cases using Apache Iceberg (open table format) and implement Medallion Architecture to ensure data quality, lineage, and accessibility.
- Build, optimize, and maintain AWS Redshift data warehouse solutions for Supply Chain analytical use cases, designing data products aligned to enterprise analytics consumption patterns.
- Define and implement Data Product-centric architecture and data mesh principles (standards for data product design, ownership, discoverability, and interoperability).
- Partner with Supply Chain BTS (IT) functional and business stakeholders to model critical data flows across SAP and planning systems; translate ERP data structures into governed, analytics-ready lakehouse data products.
- Lead a consultant technical data engineering team; supervise delivery and performance and foster engineering excellence and continuous improvement.
Qualifications:
Required:
- Bachelor’s in CS/IS/Data Engineering or related field + 7+ years (Master’s 6 years; PhD 2 years) in data architecture/engineering.
- Hands-on expertise with AWS Database & Analytics (AWS Glue, S3, EMR) and ingestion/transformation technologies (e.g., Informatica).
- Hands-on experience with Apache Iceberg (or similar) for lakehouse architecture.
- Proficiency with AWS Redshift or similar modern data warehousing.
- Experience with Medallion Architecture (Bronze/Silver/Gold) and data product frameworks; familiarity with data mesh principles.
- Familiarity with Supply Chain ERP systems (SAP) and supply chain data flows.
- Familiarity with Blue Yonder planning domain (demand/supply planning) and integration patterns.
- Strong ETL/SQL/Python and Apache Spark/PySpark skills for large-scale transformation and pipeline development.
- Knowledge of data governance frameworks, cataloging (Alation or AWS Glue Data Catalog), metadata/lineage/quality; experience implementing enterprise governance.
- Ability to analyze business requirements, evaluate options, and deliver efficient, scalable, cost-effective solutions in regulated/enterprise environments with autonomy.
Preferred:
- Knowledge of reporting tools such as Power BI.
Benefits:
- Paid time off (vacation, holidays, sick); medical/dental/vision insurance; 401(k) for eligible employees.
- Eligible for long-term incentive programs.
- Design, develop, implement, and oversee legacy ETL and cloud-native data ingestion frameworks and end-to-end data pipelines using AWS (AWS Glue, Amazon S3, AWS EMR, AWS Lambda) and ingestion/ETL tools like Informatica; assess data needs and flows to build scalable, reliable, cost-effective solutions.
- Architect Operations Supply Chain analytical use cases using Apache Iceberg (open table format) and implement Medallion Architecture to ensure data quality, lineage, and accessibility.
- Build, optimize, and maintain AWS Redshift data warehouse solutions for Supply Chain analytical use cases, designing data products aligned to enterprise analytics consumption patterns.
- Define and implement Data Product-centric architecture and data mesh principles (standards for data product design, ownership, discoverability, and interoperability).
- Partner with Supply Chain BTS (IT) functional and business stakeholders to model critical data flows across SAP and planning systems; translate ERP data structures into governed, analytics-ready lakehouse data products.
- Lead a consultant technical data engineering team; supervise delivery and performance and foster engineering excellence and continuous improvement.
Qualifications:
Required:
- Bachelor’s in CS/IS/Data Engineering or related field + 7+ years (Master’s 6 years; PhD 2 years) in data architecture/engineering.
- Hands-on expertise with AWS Database & Analytics (AWS Glue, S3, EMR) and ingestion/transformation technologies (e.g., Informatica).
- Hands-on experience with Apache Iceberg (or similar) for lakehouse architecture.
- Proficiency with AWS Redshift or similar modern data warehousing.
- Experience with Medallion Architecture (Bronze/Silver/Gold) and data product frameworks; familiarity with data mesh principles.
- Familiarity with Supply Chain ERP systems (SAP) and supply chain data flows.
- Familiarity with Blue Yonder planning domain (demand/supply planning) and integration patterns.
- Strong ETL/SQL/Python and Apache Spark/PySpark skills for large-scale transformation and pipeline development.
- Knowledge of data governance frameworks, cataloging (Alation or AWS Glue Data Catalog), metadata/lineage/quality; experience implementing enterprise governance.
- Ability to analyze business requirements, evaluate options, and deliver efficient, scalable, cost-effective solutions in regulated/enterprise environments with autonomy.
Preferred:
- Knowledge of reporting tools such as Power BI.
Benefits:
- Paid time off (vacation, holidays, sick); medical/dental/vision insurance; 401(k) for eligible employees.
- Eligible for long-term incentive programs.