** and those authorized to work in the U.S. can be considered as W2 candidates.**
Title: ETL Data Engineer
Location: San Francisco, CA
Working within the Client Data team, the MTS1 Data Engineer will be responsible for the acquisition and transformation of terabytes of new data being used to enhance the company's leverage over data and information from all of its' business units. The ETL Engineer will work with the Client Data teams to populate multi-petabyte data repositories that enable the next generation of data driven services at Client . The ideal candidate will have strong knowledge and experience creating and managing data in traditional and nontraditional ways to unlock the value and potential of the data. Previous experience in environments with big data platforms like Teradata and Hadoop is highly desirable.
•Excellent understanding of computer science fundamentals, data structures, and algorithms;
•Extensive programming experience in Scala/Java
•Experience in atleast one of the Bigdata technologies like Spark, Flink, Kafka, Mapreduce is highly desirable.
•Excellent problem solving skills
•Proficiency in SQL, Teradata SQL a plus.
•Experience in developing Bigdata visualization tools is a plus.
•Define, design, implement and test data integration modules.
•Estimate engineering effort; plan implementation, and rollout system changes.
•Must be able to independently design, code, and test major features.
•Share engineering support, release, and on-call responsibilities.
•Find and help fix stability/scalability issues in a very time critical environment.
•Utilize ETL best practices and implement them for process improvement.
•Work with external and internal teams to resolve infrastructure related issues when developing integration modules.
•Experience with agile and waterfall project development methodologies.
•Exposure and experience working in big data environments managing terabytes of data and information.
•Able to work with product managers, architects and data scientists to translate conceptual requirements into technical implementation requirements.
•Understanding of data models and data structures. Knowledge of Star Schema, Data Normalization.
•Understanding of difference between 3NF and Star Schema.
•Proficient in parallel data processing concepts.
•Highly self-motivated for success in a fast-paced, dynamic environment.
•In depth knowledge of data management systems, processes and procedures - how to acquire, understand, control and distribute data and information.
•Strong communication and organizational skills.
MS in CS with 5+ years industry experience
Bachelor's Degree with 7+ years of experience