Key Responsibilities
- Design build and maintain highly reliable scalable and performant data processing pipelines.
- Develop and maintain streaming and batch data systems leveraging technologies like Kafka Spark and Hadoop .
- Collaborate with architecture DevOps and analytics teams to integrate data solutions within cloud-based ecosystems (GCP Azure) .
- Apply strong software engineering practices ensuring code quality reusability and system resilience .
- Implement data modeling migration and transformation solutions supporting data warehousing and BI initiatives.
- Integrate with orchestration tools such as Airflow or Automic to automate and optimize data workflows.
Required Skills & Experience
Programming : Strong proficiency in Scala Python and Java (J2EE) for data processing and backend development.Big Data Technologies : Deep understanding of Hadoop Spark and distributed data frameworks.Streaming : Hands-on experience with Kafka or similar event streaming platforms.Cloud Platforms : Experience with Google Cloud Platform (GCP) or Microsoft Azure for data engineering and deployment.Data Engineering : Expertise in data modeling data migration protocols and data transformation processes.Workflow Orchestration : Practical experience with Airflow Automic or equivalent scheduling tools.Data Warehousing & BI : Familiarity with enterprise data warehouse concepts BI tools and performance optimization strategies.Best Practices : Strong focus on code quality system reliability scalability and performance optimization .Key Skills
Apache Hive,S3,Hadoop,Redshift,Spark,AWS,Apache Pig,NoSQL,Big Data,Data Warehouse,Kafka,Scala
Employment Type : Full Time
Experience : years
Vacancy : 1