Thermo Fisher Scientific is the world leader in serving science, with annual revenue of more than $40 billion. Their mission is to enable customers to make the world healthier, cleaner, and safer by supporting life sciences research, solving complex analytical challenges, increasing laboratory productivity, and improving patient health through diagnostics and the development of life-changing therapies. With a global team, they offer innovative technologies and pharmaceutical services through brands such as Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon, and PPD.
Analytical Instruments β’ Laboratory Supply Chain Programs and eCommerce β’ Laboratory Equipment β’ Lab Services β’ Specialty Diagnostics
February 28
Amazon Redshift
Apache
AWS
Cloud
DynamoDB
ETL
Informatica
Jenkins
Kafka
MongoDB
Oracle
PySpark
Python
Spark
SQL
Unity
Thermo Fisher Scientific is the world leader in serving science, with annual revenue of more than $40 billion. Their mission is to enable customers to make the world healthier, cleaner, and safer by supporting life sciences research, solving complex analytical challenges, increasing laboratory productivity, and improving patient health through diagnostics and the development of life-changing therapies. With a global team, they offer innovative technologies and pharmaceutical services through brands such as Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon, and PPD.
Analytical Instruments β’ Laboratory Supply Chain Programs and eCommerce β’ Laboratory Equipment β’ Lab Services β’ Specialty Diagnostics
β’ Work within the Enterprise data platform Delivery team to develop data driven applications and automations across a variety of infrastructure (both On-Prim and Cloud). β’ Collaboratively work in an Agile team to design, develop and maintain data structures for the Enterprise data platform. β’ Work on processes that interface with multiple systems including AWS, Oracle, Middleware and ERPs. β’ Work on development projects, pilots, and advance best design practices. β’ Lead, design, develop, deploy, and maintain mission critical data applications for Enterprise data platform. β’ Act as a technical liaison to relevant Agile delivery teams. β’ Participate in all phases of the Enterprise Data platform development life cycle as appropriate, including gathering customer requirements, defining technical requirements, creating high level architecture diagrams, data validation, and training sessions. β’ Lead different aspects of data analytics, data quality, machine learning, data acquisition, visualization, and design and analysis tasks. β’ Coordinate & work closely with architecture and data operations teams. β’ Develop documentation and training materials and participate with customer groups in planning for longer-term systems enhancements.
β’ Leading and developing BI and DW applications; β’ Data Lake, Data Analytics & Business Intelligence Solutions; β’ ETL Tools such as Informatica, Data bricks, or AWS Glue; β’ Data Lake using AWS Data bricks, Apache Spark & Python; β’ Experience in a DevOps environment, data integration and pipeline development; β’ AWS Cloud on data integration with Apache Spark, EMR, Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS, and MongoDB/DynamoDB ecosystems; β’ Development of data warehouse projects/applications (Oracle & SQL Server); β’ Python development in pySpark in AWS Cloud environment; β’ Python and common python libraries; β’ Analytical experience with database in writing complex queries, query optimization, debugging, user defined functions, views, and indexes; β’ Source control systems such as GitHub, Bit bucket, and Jenkins build and continuous integration tools.
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