The successful Team Lead will hire and lead a mix of data and software engineers to build and own big data processing infrastructure and major data pipelines to enable processing of terabytes of data a day in a distributed architecture.
Provide creative solutions for data related problems at internet scale by mixing in house and open source technologies in a cloud environment such as Kafka ,Spark, Hdfs and Snowflake.
As a lead You will be expected not only to take on end-to-end responsibilities, but also work closely with team members, collaborating with tech leadership, provide mentorship to peers, and come up with innovative ways to improve delivery.
Requirements
Bachelor’s degree in a Computer Science-related field required.
Minimum 4 years of experience in data engineering in large scale production systems.
Minimum 2 years of hands on experience in and OOP programming language.
In depth understanding of Big Data systems architecture and underlying technologies.
Good understanding in data modeling paradigms.
Practical experience in Agile methodologies including Code Reviews, CI/CD, TDD, story writing & estimation and Pair Programming.
Deep knowledge of code testing practices in main coding language (unit, integration, end to end).
A long-lasting friendship with the Linux Operating System
Experience working on a production grade data-intensive product
Large scale distributed software design and development experience. – an Advantage.
Kafka ,Spark, Hdfs, Ansible, Docker, Hive- a Strong Advantage.
TDD – an Advantage.
Teamwork and good communication skills.