Senior Engineer, Technology II (Data Engineering & Architecture)
AbbVie
August 08, 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 services including AWS Glue, Amazon S3, AWS EMR, AWS Lambda, and Informatica; assess information needs and data flows to build scalable, reliable, cost-effective solutions.
- Architect operations supply chain analytical use cases using Apache Iceberg open table format; 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, including design of data products aligned to enterprise analytics consumption patterns.
- Define and implement data product–centric architecture and data mesh principles; establish standards for data product design, ownership, discoverability, and interoperability for analytical dashboards and AI use cases.
- Partner with Supply Chain BTS (IT) 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 and supervise a technical data engineering team; ensure delivery/performance and drive continuous improvement.
Qualifications (Required):
- BS in CS/IS/Data Engineering (7+ years) or MS (6 years) or PhD (2 years) in data architecture/engineering.
- Hands-on expertise with AWS Database & Analytics (AWS Glue, Amazon S3, AWS EMR) and ingestion/transformation tech like Informatica.
- Hands-on experience with Apache Iceberg or similar lakehouse technologies.
- Proficiency with AWS Redshift or similar modern data warehousing.
- Experience with Medallion Architecture (Bronze/Silver/Gold) and data product frameworks; familiarity with data mesh (domain ownership, data product thinking).
- Familiarity with supply chain ERP systems (SAP) and supply chain data flows/domains.
- Familiarity with Blue Yonder (JDA) planning domain and integration/data model patterns.
- Strong ETL/SQL/Python and Apache Spark/PySpark skills.
- Knowledge of data governance (Alation or AWS Glue Data Catalog), metadata management, lineage, and data quality; experience implementing enterprise governance policies.
- Ability to analyze business needs, evaluate options, and deliver efficient, scalable, cost-effective solutions in enterprise/regulated environments.
Qualifications (Preferred):
- Knowledge of reporting tools such as Power BI.
Benefits:
- Paid time off; medical/dental/vision insurance; 401(k); 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 services including AWS Glue, Amazon S3, AWS EMR, AWS Lambda, and Informatica; assess information needs and data flows to build scalable, reliable, cost-effective solutions.
- Architect operations supply chain analytical use cases using Apache Iceberg open table format; 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, including design of data products aligned to enterprise analytics consumption patterns.
- Define and implement data product–centric architecture and data mesh principles; establish standards for data product design, ownership, discoverability, and interoperability for analytical dashboards and AI use cases.
- Partner with Supply Chain BTS (IT) 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 and supervise a technical data engineering team; ensure delivery/performance and drive continuous improvement.
Qualifications (Required):
- BS in CS/IS/Data Engineering (7+ years) or MS (6 years) or PhD (2 years) in data architecture/engineering.
- Hands-on expertise with AWS Database & Analytics (AWS Glue, Amazon S3, AWS EMR) and ingestion/transformation tech like Informatica.
- Hands-on experience with Apache Iceberg or similar lakehouse technologies.
- Proficiency with AWS Redshift or similar modern data warehousing.
- Experience with Medallion Architecture (Bronze/Silver/Gold) and data product frameworks; familiarity with data mesh (domain ownership, data product thinking).
- Familiarity with supply chain ERP systems (SAP) and supply chain data flows/domains.
- Familiarity with Blue Yonder (JDA) planning domain and integration/data model patterns.
- Strong ETL/SQL/Python and Apache Spark/PySpark skills.
- Knowledge of data governance (Alation or AWS Glue Data Catalog), metadata management, lineage, and data quality; experience implementing enterprise governance policies.
- Ability to analyze business needs, evaluate options, and deliver efficient, scalable, cost-effective solutions in enterprise/regulated environments.
Qualifications (Preferred):
- Knowledge of reporting tools such as Power BI.
Benefits:
- Paid time off; medical/dental/vision insurance; 401(k); eligible for long-term incentive programs.