Job Description
- Tech-savvy engineer willing to learn new skills and track industry trends.
- 5-7 years of solid data engineering experience, especially in open source, data-intensive, distributed environments, with a minimum of 5 years of experience in big data technologies like Spark, Hive, HBase, and Hadoop.
- Programming background with mandatory skills in Scala, Spark, and Java/Python.
- Experience with technologies such as MapReduce, HDFS, YARN, and Spark Streaming.
- Experience in creating end-to-end pipelines in Hadoop.
- Proficiency in SQL, Hive, and NoSQL databases.
- Experience in Linux/Unix platforms.
- Familiarity with cloud design patterns.
- Experience with Jenkins, GitHub, debugging code, and error handling.
- Experience in building end-to-end ETL pipelines.
- Self-starter with a resourceful personality and ability to manage pressure situations.
- Experience working with geographically distributed teams.
- Ability to work on high-level business and technical problems and contribute to architectural decisions.
- Experience creating core frameworks/templates for team members to start implementation/execution.
Job Responsibilities
- Build data and ETL pipelines in Hadoop.
- Support migration of data to the cloud using big data technologies like Spark, Hive, Hadoop, Scala, and Python.
- Interact with customers daily to ensure smooth engagement.
- Exposure to Google Cloud Platform (GCP).
- Responsible for timely and quality deliveries.
- Exposure to Scrum and Agile development best practices.
- Share knowledge and experience within other groups in the organization by conducting technical sessions and training.
Location
Pune, Maharashtra, India