Position: Middle/Senior Data Engineer (IRC103196)
Company: GlobalLogic
Category: Data Science
Experience required: 3y
English level: intermediate
Published: 2020-11-01T00:00:00+02:00

Description

Our Customer connects shoppers to the brands leveraging personalized digital media. Customer owns the evolving purchase history of more than three-quarters (280 million) of American shoppers. With the world’s largest shopper purchase history database driving personalized media across our networks, they drive lift and loyalty for the world’s leing retailers and CPG brands.

Requirements

Minimum of 3 years in working with Enterprise Data Warehouse technologies
Strong Experience implementing ETL processes and building data pipelines
Experience with Big Data frameworks such as Hadoop
Experience of Nifi, SOLR, and HBase is a plus
Experience with building batch- and stream-processing systems, using solutions such as Apache Spark, Kafka etc…
Experience with tuning Hadoop/Spark parameters for performance optimization
Experience with Big Data querying tools
Strong SQL programming background with the ability to troubleshoot and tune the code
Experience with cloud data platform technologies for data processing and alalysis
Multi-Dimensional Data Modeling, Data Architectures or other work related to the construction of enterprise data assets
Practical knowledge of data modeling and schema design
Excellent inter-personal and teamwork skills
Strong problem solving, troubleshooting and analysis skills
Experience working in a geographically distributed teamExperience with leading and mentorship of other engineers
Good knowledge of Agile Scrum
Good communication skills

Responsibilities

Architecture, development, orchestration and managing data processing pipelines, ETL processes for large scale data systems
Involving in design support and solutions development for the dashboards/reports deployment to various stakeholders
Work directly with the business teams for rapid prototyping of analytics solutions based on business requirements
Enterprise data warehouse processes maintenance
Tuning and performance improvements of reporting solutions
Manage cloud based data & analytics platform
Deploy updates and fixes, technical support