BS/MS in computer science or equivalent work experience.
experience in developing DB schemas, creating ETLs pipelines with Spark and familiar with MPP/Hadoop systems.
Must have mastery of data warehousing technologies including data modeling, ETL and reporting. Ideal candidate to have 6+ years of experience in end-to-end data warehouse implementations and at least 2 projects with 4TB+ data volume.
Extensive experience with databases (Vertica, Netezza or oracle and AWS data services tech).
Good knowledge of Operating Systems (Unix or Linux).
Good understanding of Data ware House methodologies.
Hands on experience in any of the programming languages (Shell scripting, Python, Java, etc).
Must have been through several full life cycle Data Warehousing implementations and involved in scalability and performance related design aspects in Database and ETL.
Solid communication skills: Demonstrated ability to explain complex technical issues related to technical and non-technical audiences.
Demonstrated understanding of the Software design and architecture process.
Experience with unit testing and data quality automation checks
Should be results oriented, self-motivated, accountable and work under minimal supervision.
Excellent written, oral communication and presentation Skills.
Good to have
Knowledge of Big Data eco system like Hadoop M/R, Pig and Hive is a strong plus.
Conceptual understanding of Machine Learning / LLM / GenAI Usage is a plus.
Good understanding of any reporting tools such as Tableau, QlikSense
Experience in design, development and deployment of one or more tools - ETL (Informatica, OWB, ODI )