Data Engineer

Requirement Detail
5 years of experience in a Data Engineer role, with a Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
•          Knowledge of programming languages (e.g. Java and Python)
•          Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
•          Great numerical and analytical skills
•          Data engineering certification (e.g IBM Certified Data Engineer) is a plus
•          Create and maintain optimal data pipeline architecture
•          Analyze and organize raw data?????
•          Assemble large, complex data sets that meet functional / non-functional business requirements.
•          Prepare data for prescriptive and predictive modeling
•          Build algorithms and prototypes
•          Combine raw information from different sources
•          Explore ways to enhance data quality and reliability
•          Create data tools for analytics and data scientist team members
•          Working with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues
•          Working with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues
•          Work with data and analytics experts to strive for greater functionality in our data systems.
•          Collaborate with data scientists and architects on several projects
•          Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
•          Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
•          Experience supporting and working with cross-functional teams in a dynamic environment.
•          Build processes supporting data transformation, data structures, metadata, dependency, and workload management