A career is an ongoing journey of discovery: our 52,000 people are shaping how the world lives, works and plays through next generation advancements in healthcare, life science and performance materials. For 350 years and across the world we have passionately pursued our curiosity to find novel and vibrant ways of enhancing the lives of others.
Text Analytics Engineer is expected to support internal projects and products by building data pipelines for data ingestions from source systems, data transformation, data curation, and ingestion to target systems with heavy focus on text data such as clinical trials, publications, patents, social media, and internal legacy documents (PDFs, WORD files) stored in RDBMS systems. He/She needs to ensure that data pipelines adhere to internal engineering standards, they are robust and ready for operational use in terms of good documentation and solid testing.
1. Atleast 4 years of hand-on experience in building data pipelines and ETL/ELT running within Hadoop environment
2. Strong programming skills in Scala and/or Java is a must. Python skills are welcome.
3. Solid working knowledge of components of Hadoop ecosystem such as HDFS, Hive, Spark, Sqoop, Oozie, Kafka, Atlas.
4. Has developed pipelines to support text mining, text analytics, or natural language processing projects.
5. Good understanding of document indexing systems such as Elasticsearch, Solr or Lucene
6. Backgroud of software engineering, data engineering, software development is an assett
7. Experience in processing text data and documents (especially PDF and WORD formats) is an asset
8. Working experience with common data exchange formats such as XML and JSON
9. Integration experience with analytics and reporting applications such as Qlik, Spotfire, Kibana, Tableau is an asset (not mandatory)
10. Experience working in pharmaceutical industry (GxP/GAMP environment) is a plus
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