Senior Azure Databricks Engineer- Only Locals

Required skills:

• 15+ years of experience in IT.
• Heavy ADF (Azure Data Factory): Azure Engineering, DW, Data pipelines, Data Lakehouse, Databricks
• Very technical, hands-on- not looking for Architects
• Love ETL Development, Database exp
• ADF (Azure Data Factory):Azure Engineering, Data warehouse, Data pipelines, Databricks, Data lakehouse, ETL, Strong Database experience.
• Experience in the following domains is ideal: Banking, Insurance, Healthcare.
• Experience on ADLS, Azure Databricks, Azure SQL DB and Datawarehouse
• Strong working experience in Implementation of Azure cloud components using Azure Data Factory , Azure Data Analytics, Azure Data Lake, Azure Data Catalogue, LogicApps and FunctionApps
• Have knowledge in Azure Storage services (ADLS, Storage Accounts)
• Expertise in designing and deploying data applications on cloud solutions on Azure
• Hands on experience in performance tuning and optimizing code running in Databricks environment
• Good understanding of SQL, T-SQL and/or PL/SQL
• Should have experience working in Agile projects with knowledge in Jira
• Good to have handled Data Ingestion projects in Azure environment
• Demonstrated analytical and problem-solving skills particularly those that apply to a big data environment
• Experience on Python scripting, Spark SQL PySpark is a plus.

Responsibilities:

• Build large-scale batch and real-time data pipelines with data processing frameworks in Azure cloud platform.
• Designing and implementing highly performant data ingestion pipelines from multiple sources using Azure Databricks.
• Direct experience of building data pipelines using Azure Data Factory and Databricks.
• Developing scalable and re-usable frameworks for ingesting of datasets
• Lead design of ETL, data integration and data migration.
• Partner with architects, engineers, information analysts, business, and technology stakeholders for developing and deploying enterprise grade platforms that enable data-driven solutions.
• Integrating the end-to-end data pipeline - to take data from source systems to target data repositories ensuring the quality and consistency of data is maintained at all times
• Working with event based / streaming technologies to ingest and process data
• Working with other members of the project team to support delivery of additional project components (API interfaces, Search)
• Evaluating the performance and applicability of multiple tools against customer requirements

Regards,

Raj Dakshinapu | Recruiter, Dotcom Team LLC

Phone:

Web: | Email:

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