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About the role
Strong experience in ADF( Azure data factory), Azure SQL, Synapse, Spark/Databricks= 5+ Yrs Excellent written and verbal communication, intellectual curiosity, a passion to understand and solve problems, consulting & customer service Structured and conceptual mindset coupled with strong quantitative and analytical problem-solving aptitude Exceptional interpersonal and collaboration skills within a team environment PySpark Parquet files Big data and modern data lake Demonstrable experience in enterprise level data platforms involving implementation of end-to-end data pipelines Hands-on experience with Azure Experience with column-oriented database technologies (e.g., Synapse), NoSQL database technologies (e.g., DynamoDB, Cosmos DB, etc.) and traditional database systems (e.g., SQL Server, Oracle, MySQL) Experience in data pipelines and solutions for both streaming and batch integrations using tools/frameworks like Azure Data Factory, Azure functions and Stream analytics Metadata definition and management via data catalogs, service catalogs, and stewardship tools such as OpenMetadata, and Azure Purview Test, plan, creation and test programming using automated testing frameworks, data validation and quality frameworks, and data lineage frameworks Data modeling, querying, and optimization for relational, NoSQL, timeseries, graph databases, data warehouses and data lakes Data processing programming using SQL, Python, and similar tools Logical programming in Python, Spark, PySpark, Java, Javascript, and/or Scala Cloud-native data platform design with a focus on streaming and event-driven architectures Participate in integrated validation and analysis sessions of components and subsystems on production servers Data ingest, validation, and enrichment pipeline design and implementation SDLC optimization across workstreams within a solution Bachelor’s degree in Computer Science, Engineering, or related field
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