In this role as a Snr Data Engineer, reporting into a new team in the Finance organization as a Center of Excellence for Data Science, you will be at the intersection of data science, analytics, and data visualization to produce new business insights and drive decision making within a world-leading life science company.
You will be responsible for creating the technology that moves and translates data used to inform our most critical strategic and real-time decisions. You will also help translate business needs into requirements and identify efficiency opportunities. In addition to extracting and transforming data, you will be expected to use your expertise and provide meaningful recommendations and actionable strategies to partnering data scientist for performance enhancements and development of best practices, including streamlining of data sources and related programmatic initiatives. The ideal candidate will have a passion for working in white space and creating impact from the ground up in a fast-paced global environment.
Create and develop organized databases for use in data science projects and initiatives
Design, build and launch efficient & reliable data pipelines to move and transform data (both large and small amounts)
Intelligently design data models for optimal storage and retrieval
Deploy inclusive data quality checks to ensure high quality of data
Optimize existing pipelines and maintain of all domain-related data pipelines
Ownership of the end-to-end data engineering component of the solution
Collaboration with the Data Center SMEs, Data Scientists, and Program Managers
Design and develop new systems in partnership with software engineers to enable quick and easy consumption of data
Skills and Qualifications:
BS/MS in Computer Science or a related technical field
5+ years of SQL (Oracle, Vertica, Hive, etc.) experience and relational databases experience (Oracle, MySQL)
5+ years of experience in custom or structured (i.e. Informatica/Talend/Pentaho) ETL design, implementation and maintenance
5+ years' experience in data engineering, experience in applying DWH/ETL best practices
5+ years' of Java and/or Python development experience
2+ years' experience in LAMP and the Big Data stack environments (Hadoop, MapReduce, Hive)
2+ years' experience working with enterprise DE tools and experience learning in-house DE tools
Natural bias towards continuous process improvement
Skilled in real-world data handling, particularly in situations involving sparse and/or incomplete data sets.
Understanding of impact and application for finance, accounting reporting systems
Experience with Hyperion Planning, Cognos, ERP or similar systems are considered an advantage