Role :
Junior Data Engineer
Location :
India - Bangalore IT
JOB DESCRIPTION:
Data and analytics excellence at Dyson is delivered by a diverse and collaborative global community, at the heart of that community is a hub team that enables all others: In Dyson’s Data Analytics team, there has been significant investment into cloud technologies and tools; combined with an expansive scope and no shortage of ambition and momentum, Dyson Data Analytics team is recognised throughout the organisation to the highest level as critical to all of Dyson’s strategic objectives.
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What you will do
The Role
At Dyson, Data Engineers are Software Engineers specialising in building data intensive applications.
You will be responsible for:
Delivering Data Engineering excellence in the end-to-end delivery of complex data engineering projects and programs for Dyson
Reviewing technical designs and providing feedback
Designing and building end-to-end data solutions for analytics
Migrating existing pipelines onto the platform
Involve in deployment, testing activities with hands on engineering and automation experience including CI/CD/CD and DataOps mindset
Adapting quickly to change in requirements and be willing to work with different technologies if required
Develop and maintain data pipelines in a Backend/Distributed Data Systems team while remaining hands-on is very important
Strengthening data quality and reliability
Improving data lineage and governance
Progressing standards and best practices for the platform and operational excellence
Maintaining our documentation culture
Education Required:
Have 1-2 years of relevant experience
Write clean code that can be easily understood by others
Be able to understand and improve legacy code
Identify and build abstractions and tools to solve recurring challenge
Apply best practices and ways of working among our global data engineering team
Provide constructive feedback through PRs and pairing
Seek to close gaps in documentation
skills
Have 1-2 years of relevant experience
Write clean code that can be easily understood by others
Be able to understand and improve legacy code
Identify and build abstractions and tools to solve recurring challenge
Apply best practices and ways of working among our global data engineering team
Provide constructive feedback through PRs and pairing
Seek to close gaps in documentation
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