Contract Duration: 11 Months
Design, develop, test, deploy, support, enhance data integration solutions seamlessly to connect and integrate ThermoFisher enterprise systems in our Enterprise Data Platform.
Innovate for data integration in Apache Spark-based Platform to ensure the technology solutions leverage cutting edge integration capabilities.
Facilitate requirements gathering and process mapping workshops, review business/functional requirement documents, author technical design documents, testing plans and scripts.
Assist with implementing standard operating procedures, facilitate review sessions with functional owners and end-user representatives, and leverage technical knowledge and expertise to drive improvements.
4+ years working experience in data integration and pipeline development.
BS degree in CS, CE or EE.
2+ years of Experience with AWS Cloud on data integration with Apache Spark, EMR, Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS, MongoDB/DynamoDB ecosystems
Strong real-life experience in python development especially in pySpark in AWS Cloud environment.
Design, develop test, deploy, maintain and improve data integration pipeline.
Experience in Python and common python libraries.
Strong analytical experience with database in writing complex queries, query optimization, debugging, user defined functions, views, indexes etc.
Strong experience with source control systems such as Git, Bitbucket, and Jenkins build and continuous integration tools.
Databricks or Apache Spark Experience is a plus.
Highly self-driven, execution-focused, with a willingness to do what it takes” to deliver results as you will be expected to rapidly cover a considerable amount of demands on data integration
Understanding of development methodology and actual experience writing functional and technical design specifications.
Excellent verbal and written communication skills, in person, by telephone, and with large teams.
Strong prior technical, development background in either data Services or Engineering
Demonstrated experience resolving complex data integration problems;
Must be able to work cross-functionally. Above all else, must be equal parts data-driven and results-driven.