Senior Data Engineer

Job Description
Data Science and Analytics is an ambitious team of Data Scientists and Data Engineers with a unique blend of Business, Scientific, and Machine Learning expertise that seeks to unleash the full potential of AbbVie’s data assets by bringing technology and/or data and insights to the forefront of decision making via fit-for-purpose solutions.
The Data Engineer role in DSA is a unique role with blend of data engineering responsibilities in the context of Data Science/ML and AI. A key role to enable application of advanced analytics techniques across clinical development processes. Drives analytics innovation and experimentation to enable data-driven insights for complex business problems across R&
D by deploying advanced analytics techniques like Machine Learning and Visual Analytics.
Responsibilities:
Collaborates with the Data Scientists and cross-functional data stewards to identify appropriate data sources and to enable streamlined data flow for the Data Science and Analytics capabilities across clinical development.
Develop, construct, test and maintain architectures (such as databases and large-scale process systems) to support strategic projects within Clinical Development
Build data products and processes which perform data transformation, metadata extraction, workload management and error processing and management.
Implement standardized, automated operational and quality control processes to deliver accurate and timely data and reporting.
Adhere to best practices for coding, testing and designing reusable code/component.
Contribute to the discovery and understanding of new tools, techniques and technologies to change course as needed.
Develop solutions to improve data reliability, efficiency and quality.
Ensures adherence to federal regulations and applicable local regulations, Good Clinical Practices (GCPs), ICH Guidelines, AbbVie Standard Operating Procedures (SOPs), and to functional quality standards. Stays abreast of new and/or evolving local regulations, guidelines and policies related to clinical development.
Self-starter, comfortable with ambiguity, experience initiating and driving projects with minimal oversight and guidance.
Establish and follow data science and engineering best practices including peer review, code review, documentation, coding standards, data quality and ensure reproducibility and compliance.
Highly autonomous and productive in accomplishing the deliverables with minimal direction.
Tools and skills you will use in this role:
Advanced SQL and Python/R
Working with databases like Oracle, Microsoft SQL server etc.
Data Cataloging platform like Alation etc.
Cloud platform like AWS and/or Azure, including but not limited to services like S3, EC2, EMR, MWAA, etc.
ETL, Orchestration and scheduling tools like Informatica and Airflow
JIRA, Confluence and agile project methodology
Interaction with BI tools like PowerBI, Tableau and Spotfire, Web app platforms like Plotly Dash, RShiny etc.