Work location Bangalore
Work from office
Strong Databricks knowledge is a must and the candidate has to be willing to work in support engagement (prior experience would be good). If this skill is not there, will not consider the profiles .
Experience required
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Total 6 - 9 years of experience and relevant 3 - 4 years of experience in Azure Databricks
Extensive traditional and cloud based BI development work in commercial environments
Manage and maintain all aspects of ETL from development, bug fixing, batch job monitoring
Provide 'hands on' technical support and escalation (through Incident, Change & Problem Management procedures) and to ensure that SLAs are achieved, whilst also looking for ways to improve the day-to-day IT delivery
Hands on experience in Implementation, design and Management of releases and deployments
Ability to clearly communicate complex solutions
Flexibility to support P2 issues arising during non-working hours, holidays, and weekends
Technical skills required
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In-depth experience in data warehousing concepts - ELT, Data Modelling techniques.
The ability to design and advocate for technical solutions to business problems.
Strong understanding of delta (batch) processing, slowly changing dimensions, data marts.
Strong knowledge of SQL (Hive SQL is a plus)
Comprehensive experience in developing ETL using Data Bricks
Basic knowledge of Spark architecture is a plus
Experience with Databricks/Snowflake environment configuration and management
Experience with Git, specifically Azure DevOps
Knowledge of, or ability to quickly pick-up components CI/CD Pipelines, Erwin Data Modeller
Ability to contribute to all aspects of a solution - design, infrastructure, development, testing and maintenance
Strong work experience in production issue resolution
Technology experience in SQL, Databricks/ Hadoop/ Spark
Experienced in a variety of DW tools and products including Oracle DB, Snowflake, Talend, Azure, Hadoop, etc. will be good to have
Experienced in working under pressure and with tight deadlines

Keyskills: azure data engineer databricks data bricks