Big Data Scientist( Engineer)

Key Responsibilities:

• Work together with product owners and solution architects to translate and formulate business requirements into technical specifications of the data platform.

• Lead and manage a team of data engineers to implement robust, scalable, and efficient data refinery-related solutions using the appropriate data engineering or big data engineering techniques.

• Data ETL and data analysis for structured/unstructured and streaming data.

• Work together with AI scientists to integrate data pipeline with ML pipeline.

• Support technical director with resource planning and budgeting for data refinery and AI projects.
  

Requirements :

• MEng/Ph.D. with a minimum of 5-7 years of work experience in data engineering.

• Working experience on big data tools such as Hive, Hadoop, Spark, Elastic Stack, Kafka, and databases (Cassandra, MongoDB, and Neo4J) is preferred.

• Demonstrated leadership to solve complicated data engineering or data science-related technical problems.

• Familiar with Cloud Computing platforms & its ML Cloud Services, such as AWS SageMaker, Google ML Engine, and MS Azure Machine Learning Studio.

• Excellent communication skills. Able to explain complicated technical concepts using simple and understandable language to an audience who do not have a strong technical background.