Lead Data Engineer - Spark, Scala

Responsibilities

• Design, development and testing of components / modules involving Spark, Scala, Hive and related big-data technologies in a datalake architecture
• Implement design, development and deployment of new Data pipelines and maintain the existing ones.
• Lead migrations such as move to public cloud ( Azure ), version upgrades.
• Oversee team of Data Engineers located in both offshore and onshore.
• Building views that are plugged by Data Visualization tools such as Power BI Release & Deployment – Deploy using CD/CI practices and tools in various environments – development, UAT and production and follow production processes.
• Ensure Craftsmanship practices are followed.
• Follow Agile@Scale process in terms of participation in PI Planning and follow-up, Sprint planning, Back-log maintenance in Jira.
• Develop/propose tactical solutions for Project specific needs

• 7 + years of experience as a Data Engineer
• Architect, Design, Develop code on Spark, Scala, Hive, any big data ecosystem, 
  Python, SQL, Design Patterns, Design Principles and Functional Patterns .
• Good understanding of ETL Processes and data warehousing concepts, API's
• Expertise in Spark, Scala, Unix Shell Scripting
• Good Hands on SQL, experience of Power BI will be added advantage.
• Working experience on public Cloud preferably on Azure will be an added advantage.
• Should have experience on Releasing, CI/CD, Git and JIRA
• Good analytical and troubleshooting skills to resolve the issues in timebound manner.
• Effective team player with ability work autonomously and in team with cross-cultural environment
• Effective verbal and written communication to work closely with all the stakeholders

Mandatory Skills:

Should be strong in Spark, Scala, Hive, SQL, Data Modeling

Good to Have Skills:

Azure, Databricks, Python, BI Reporting, AI

CI/CD, AGILE

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