At least 8 years of overall experience in building ETL/ELT, data warehousing and big data solutions.
At least 5 years of experience in building data models and data pipelines to process different types of large datasets.
At least 3 years of experience with Python, Spark, Hive, Hadoop, Kinesis, Kafka.
Proven expertise in relational and dimensional data modeling.
Understand PII standards, processes, and security protocols.
Experience in building data warehouse using Cloud Technologies such as AWS or GCP Services, and Cloud Data Warehouse preferably Google BigQuery.
In depth knowledge in Big Data solutions and Hadoop ecosystem.
Strong SQL knowledge - able to translate complex scenarios into queries. Strong Programming experience in Java or Python. Experience in Google Cloud platform (especially BigQuery & Dataflow).
Experience with Google Cloud SDK & API Scripting. Experience in Hadoop (Hive, MapReduce, Spark).
Experience in Onsite-Offshore coordination. Experience in Test Driven Development. Experience in Agile processes and DevOps methodologies.
Experience in NoSQL Databases. Experience with Data modeling and mapping. Experience of Retail domain will be an added advantage.
Google Cloud Professional Data Engineer Certification is an advantage. Programming Language - Java / Python. Google Cloud - Big Query, Pub/ Sub, Dataflow, Composer DAGs, Cloud storage. CI/CD - GitHub, Jenkins.
Required Skills:
Good organizational and problem-solving skills
Good team player who is self motivated and well organized