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Duties: Convert complex business problems into elegant data solutions in Bigdata using advanced technologies like Python, Spark, Postgres, Advanced Analytics, Hadoop, Greenplum. Partner with the business to gather requirements through understanding of business users' data/analytics needs and challenges. Apply in-depth understanding of Asset Management business and use data to solve complex business problems. Collaborate with Senior Associates to lead different parts of data solution delivery along with internal technology, vendor and business partners. Design and develop feature sets for Machine Learning algorithms. Contribute to all aspects of development across multiple layers of the data platform. Develop quality controls across all products. Perform testing of both functional and non-functional aspects, leveraging and promoting automation and a test-early and often approach. Collaborate with business, technology, and vendor partners to identify options, analyze pros and cons, and assist in making recommendations to business and IT stakeholders. Research and execute proof of concept of new technologies to accelerate business delivery and automate processes. Plan, estimate and create work break down activities on projects. Proactively identify and communicate issues, risks, progress to business and IT stakeholders, providing options and next steps. Troubleshoot and support the entire product, across all layers of the data platform.
Minimumeducation required: Bachelor's degree orequivalent in Electronic Engineering, or related field.
Minimumexperience required: 4 years of experience infinancial data modeling in big data environments , or related experience.
Skillsrequired: Experience in Data Modelling, Application Security, and Data Architecturein Bigdata environments. E xperience delivering data solutions, including datawarehousing, reporting and analytics in Bigdata environments. Demonstratedknowledge of Bigdata Technologies including Greenplum, Hadoop, Spark, Hive andImpala. Experience in optimizing queries and code across large data sets.Experience with Jenkins, Git, and Stash for continuous integration and securityreviews. Demonstrated technical knowledge of ETL and ELT technologies andimplementation with tools including Pentaho. Experience with specializedprogramming languages: Python, Scala, Spark, and Postgres. Experience with machinelearning, quantitative analytics and statistical techniques. Demonstratedknowledge of Business Processing. Demonstratedknowledge of the financial industry, data and technology. Demonstrated knowledge of third-partydata management integration and reporting. Employer will accept any amountof professional experience with the required skills.