About the Role
- Experience in end-to-end data architecture and design, including ingestion , modeling , storage , and orchestration (ex. Medallion).
- Proficiency in cloud-native engineering, with a focus on Microsoft technologies (Fabric, Azure Data Factory, Synapse ) but open to other cloud platforms (AWS, Google Cloud) with comparable tools.
- Hands-on experience with data warehousing and data lake solutions (e.g., BigQuery, Azure Data Lake, Delta Lake, Amazon Redshift ).
- Proficiency in programming languages such as Python (with data-related libraries: e.g. Pandas, Boto3), SQL , or Spark .
- Strong knowledge of RDBMS (e.g., Oracle, MS SQL Server) or NoSQL databases (e.g., MongoDB, ElasticSearch, GBQ).
- Experience with DevOps/DataOps practices, including CI/CD pipelines.
- Ability to implement data validation, lineage, documentation, and monitoring at s...
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