Job Duties: Diverse Data Engineering activities on Azure Data platform including Azure Databricks.
Build & Deliver Data pipeline connecting various enterprise data sources both RDBMS, NoSQL & APIs. Develop data mappings to existing data sources.
Develop data requirements for new data sources.
Design and development of data extraction, data ingestion, data quality rules implementation
Understand the data model, transform data to target schema from relational and semi structured source data.
Scripting and programming using programming languages such as Python, PySpark etc.
Involvement in architecture and design of data
Work with Data Governance team to implement Data Quality and Security guidelines
Work with DevOps team to implement CI/CD pipelines
Minimum Skills Required: 4+ years overall experience in data domain (data analysis, database developer)
Minimum 3 years experience as a cloud-based Data Engineer preferably Databricks
Minimum 3 years experience and strong knowledge of Azure Data Services such as Azure Data Lake Storage, Blob Storage, Azure Data Factory,
Minimum 3 years experience on Apache Spark or Azure Databricks. Good hands on skills working with Python, PySpark, and SparkSQL
Good understanding of data integration and warehousing (ETL, ELT) processes
Strong knowledge of Database concepts, SQL and experience in working with Database clients like, TOAD, SQL developer, SQL Server Management Studio
Good knowledge of NoSQL/ Document DB.
Good understanding of Enterprise Information Model and Enterprise Data Warehouse
Proficient in analyzing business requirements and mapping them to technical requirements
Data Analysis and Interpretation, and Data Issue Debugging Skills
Good knowledge of DevOps tools and processes as it applies to Data Engineering"
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Keyskills: Azure azure databricks continuous integration data services python data analysis azure data lake blob storage toad ci/cd pyspark azure data factory elt data engineering sql nosql data bricks ssms spark database creation devops data integration