Support Data Science team by applying data mining techniques, feature engineering, algorithm optimization and scaling machine learning models in big data, cloud environment
Support data aggregation jobs in a production environment as well as tune and optimize existing code base for multiple data products
Process structured and unstructured data, validate data quality, and help design data quality tests in a big data environment
Facilitate end to end solution design reviews with other members of the team that include communicating design, requirements, feature sets, functionality and limitations of systems/applications
Build data movement pipelines leveraging SQL, Python and Spark that meet all functional & non-functional requirements
Develop efficient feature capabilities to support proper data extraction & curation for analytical purposes
Develop self-service analytics to enable users to better understand and assess impacts of key business drivers on financial results.
Minimum Qualifications
5+ years working as data engineer / database developer (Hadoop, cloud experience preferred)
5+ years of experience in data warehousing / big data environment, preferably in wireless industry and/or finance function
Experience building & optimizing data pipelines on cloud solutions such as AWS & Azure
Extensive experience in Spark, Python, PySpark, Scala, SQL/Hive
Familiar with Spark MLlib, SParkSQL
Writing complex SQL statements and performing data discovery
Proven experience with data modeling, complex data structures, data processing, data quality, and data lifecycle
Experience in API design, SDK architecture, and mobile software lifecycle development practices
Strong organizational and time management skills, ability to prioritize a large group of diverse projects simultaneously, and deliver on multiple threads of work
Experience working in agile environments on multiple projects simultaneously
Excellent written and verbal communication skills
Bachelor’s degree in computer science or related technical field