Role Description :
Data engineering role requires creating and managing technological infrastructure of a data platform, be in-charge / involved in architecting, building, and managing data flows / pipelines and construct data storages (noSQL, SQL), tools to work with big data (Hadoop, Kafka), and integration tools to connect sources or other databases. Should hold minimum 5 years of experience in DBT and Snowflake.
Role Responsibility :
- Translate functional specifications and change requests into technical specifications
- Translate business requirement document, functional specification, and technical specification to related coding
- Develop efficient code with unit testing and code documentation
Role Requirement :
Proficient in basic and advanced SQL programming concepts (Procedures, Analytical functions etc.)Good Knowledge and Understanding of Data warehouse concepts (Dimensional Modeling, change data capture, slowly changing dimensions etc.)Knowledgeable in Shell / PowerShell scriptingKnowledgeable in relational databases, non-relational databases, data streams, and file storesKnowledgeable in performance tuning and optimizationExperience in Data Profiling and Data validationExperience in requirements gathering and documentation processes and performing unit testingUnderstanding and Implementing QA and various testing process in the projectAdditional Requirement :
Design, develop, and maintain scalable data models and transformations using DBT in conjunction with Snowflake, ensure the effective transformation and load data from diverse sources into data warehouse or data lake.Implement and manage data models in DBT, guarantee accurate data transformation and alignment with business needs.Utilize DBT to convert raw, unstructured data into structured datasets, enabling efficient analysis and reporting.Write and optimize SQL queries within DBT to enhance data transformation processes and improve overall performance.Establish best DBT processes to improve performance, scalability, and reliability.Expertise in SQL and a strong understanding of Data Warehouse concepts and Modern Data Architectures.Familiarity with cloud-based platforms (e.g., AWS, Azure, GCP).Migrate legacy transformation code into modular DBT data models.Skills Required
Azure Data, Python, Sql, Qa Tester, Powershell Scripting, Aws