Senior Data and Analytics Engineer

The Senior Data and Analytics Engineer will be responsible for translating complex business and data requirements into scalable secure and high-performing analytics and data engineering solutions for the Operations (Supply Chain) organization. The role will partner closely with internal DATA (Data AI Transformation and Automation) teams and cross functional Business Technology Solutions (BTS) business stakeholders architects and delivery teams to understand strategic priorities and design build and deliver modern data solutions that enables analytics business intelligence and AI use cases. 

This role requires a strong combination of hands-on technical expertise and strategic thinking understanding the North Star platform architecture to implement practical engineering solutions while ensuring alignment with enterprise architecture development standards data governance security and engineering best practices.

The individual will also provide technical leadership throughout the solution lifecycle proactively manage technical risks and dependencies and communicate effectively with both technical and business stakeholders. 

Responsibilities 

• Hands-on engineering and solution delivery: Design develop test deploy and support production-grade data pipelines and data products for structured semi-structured and unstructured data. Build for both batch and near-real-time/streaming patterns with reusable components parameterized frameworks and automated recovery. 
• Lakehouse and modern data warehouse architecture: Implement solutions using Amazon S3 Apache Iceberg/open table formats AWS Glue Data Catalog Amazon EMR/Spark Amazon Redshift and Redshift Spectrum. Apply medallion patterns (Bronze Silver Gold) dimensional and domain-oriented modeling workload isolation partitioning clustering/sort strategies and performance optimization. 
• Data product and data mesh enablement: Translate business domains into discoverable interoperable and governed data products. Define product contracts ownership metadata quality expectations service-level objectives lineage and approved consumption patterns for dashboards self-service analytics APIs data science and AI. 
• Ingestion and orchestration: Engineer reliable ingestion from enterprise applications databases files APIs and event streams. Develop orchestration using tools such as Apache Airflow dbt AWS Step Functions or equivalent approved platforms with dependency management idempotency observability alerting and backfill capability. 
• Data quality governance and security: Embed automated data-quality controls reconciliation schema validation lineage cataloging retention encryption least-privilege access and auditability. Partner with data governance security privacy architecture and platform teams to meet AbbVie standards and regulated-industry expectations. 
• DevSecOps and engineering excellence: Establish source-control code-review automated testing CI/CD infrastructure-as-code environment promotion release management and operational monitoring practices. Improve reliability cost performance and developer productivity through measurable engineering standards. 
• Business partnership and technical leadership: Understands organizations vision goals and strategies and partner with DATA BTS Operations stakeholders to translate complex requirements into scalable designs. Provide technical direction resolve design and delivery issues communicate risks and trade-offs and contribute to portfolio prioritization and roadmap decisions. 
• Operational ownership: Own solutions through the full lifecycle including production readiness deployment support transition incident resolution root-cause analysis technical debt reduction and continuous improvement. Work with minimal oversight while escalating material risks early. 

Qualifications :

Required:

• Bachelors Degree in Computer Science Information Systems Data Engineering or a related field plus 7 years of relevant experience; Masters Degree plus 6 years of experience; PhD plus 2 years of experience. 
• Respective years of hands-on experience designing and delivering enterprise modern data warehouse Lakehouse data engineering and analytical solutions. 
• Advanced proficiency in SQL and Python with strong hands-on experience in PySpark or Scala and distributed data processing on Apache Spark/EMR or a comparable platform. 
• Demonstrated experience building large Lakehouse and modern warehouse solutions using Amazon S3 Apache Iceberg or comparable open table formats AWS Glue Amazon EMR Amazon Redshift and Redshift Spectrum. 
• Proven experience with medallion architecture data modeling schema design incremental processing change data capture partitioning performance tuning and cost optimization. 
• Experience developing production-grade batch and streaming data pipelines including orchestration retries backfills observability alerting and operational support. 
• Hands-on experience with data transformation and orchestration tools such as Apache Airflow AWS Step Functions or approved equivalents. 
• Experience implementing CI/CD automated testing Git-based development infrastructure-as-code and Agile DevOps delivery practices. 
• Demonstrated ability to build governed AI-ready data products that support BI self-service analytics data science machine learning and contextual AI consumption. 
• Strong analytical problem-solving communication and stakeholder-management skills with the ability to work effectively across technical and business teams in a matrixed organization. 
• Experience with data catalogs lineage and governance platforms such as Alation AWS Glue Data Catalog or approved equivalents. 

Preferred: 

• Supply Chain or Operations domain knowledge across planning sourcing inventory manufacturing logistics or distribution. 
• Experience with streaming technologies such as Amazon Kinesis Apache Kafka Spark Structured Streaming or equivalent platforms. 
• Working experience with AWS Lake Formation IAM Secrets Manager CloudWatch CloudTrail and enterprise controls for secure data platforms. 
• Experience exposing data through APIs semantic models governed data services or feature/context layers for AI-enabled applications. 
• Relevant cloud or data engineering certifications are beneficial but not required. 
• 5 years of hands-on experience designing and delivering enterprise modern data warehouse Lakehouse data engineering and analytical solutions. 

Additional Information :

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: 

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location and we may ultimately pay more or less than the posted range. This range may be modified in the future. 

• We offer a comprehensive package of benefits including paid time off (vacation holidays sick) medical/dental/vision insurance and 401(k) to eligible employees.

• This job is eligible to participate in our long-term incentive programs. 

Note: No amount of pay is considered to be wages or compensation until such amount is earned vested and determinable. The amount and availability of any bonus commission incentive benefits or any other form of compensation and benefits that are allocable to a particular employee remains in the Companys sole and absolute discretion unless and until paid and may be modified at the Companys sole and absolute discretion consistent with applicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity driving innovation transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. 

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Work :

No

Employment Type :

Full-time