Identify and develop a strategy on long term data architecture, to build effective data-driven decisions to optimize customer’s experience
Design, build, and deliver cloud-based big data platform, components and services
Automate end-to-end data pipelines, making datasets readily consumable and available for ML models, and in-house visualization tools.
Collaborate with multiple engineering or product teams, able to analyze and generate reports to stakeholders and help the team to improve products and content performances.
Establish solid and best engineering practices for engineers as well as non-technical people
3+ years of industry experience in software development, data engineering, or analytics with track record of delivering large scale data platform
BS or MS in Computer Science, Mathematics, or a related technical field or equivalent practical experience.
Demonstrated strength in data modeling, data access, data storage strategies
Experience with at least one of the following cloud platforms is a plus (e.g. AWS, GCP, or Azure)
Background with distributed framework (e.g. Spark, Hadoop, Flink, Kafka Streams).
Workflow management or data pipelines (e.g. Airflow, Luigi, Jenkins).
Experience with relational databases (e.g. MySQL), exposure to no-SQL appliances and a variety of databases (e.g. Dynamo, Elastic Search, Kafka, Hive, etc.)
Experience in writing software for data extraction and transformation in one or more languages (e.g. Python, Scala, or Java)
Good understanding of UNIX/LINUX environments
