Job Responsibilities

• Lead development and execution of data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs.
• Demonstrate a deep knowledge of, and ability to operationalize, leading data technologies and best practices in order to identify and assess critical capabilities and recommend solutions.
• Designs and modifies components of new and existing IT systems to promote integrated corporate business systems.
• Data visualizations via R or D3 a plus
• Experience with implementing complex, enterprise-wide data transformation and processing solutions
• Experience with data in various forms (data warehouses/relational SQL, NoSQL, JSON, unstructured data environments/PIG, HIVE, Impala)
• Experience with AWS Data Pipeline, Kinesis and Glue a plus
• End-to-end SDLC experience a plus

Job Requirements

• Degree in Computer Science, equivalent engineering degree, or relevant practical experience.
• 5 years of progressively complex related experience.
• High proficiency in SQL (ANSI) with the ability to write complex freehand SQL including sub-queries, nested queries, and other advanced SQL features.
• Experience with reporting platforms (Microstrategy, Domo, OBIEE, Qlik View, etc. – SAP Business Objects ++)
• Experience with data discovery tools (Tableau, etc.).
• Experience with a RDBMS (IBM DB2, Netezza, MySQL a plus).
• Proven experience with development and scripting in Java, Object-Oriented Languages, Python or any of the major languages to build robust data pipelines and dynamic systems.
• Proven ability to leverage multiple tools and programming languages to analyze and manipulate data sets from disparate data sources and build innovative solutions.
• Proven knowledge of AWS including services in their compute, storage, databases, management tools, and analytics portfolio. (open to GCP/Azure equivalents)
• A passion for data, and an understanding of how to work with large data sets consisting of as well as willingness to learn new technologies and methodologies under minimum guidance