Senior Azure Data Engineer

Senior Azure Data Engineer

Location: Hybrid in Charlotte (final round is face to face in NJ office though)

6+ years exp (8+ preferred) Databricks, data lake, data factory, azure suite, pyspark, PowerBI (reports, visualization). PowerBI is a must now as reporting piece is coming into scope.

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.
• Utilize version control systems such as GitHub for managing code, collaboration, and maintaining repository integrity.
• Implement and maintain materialized views, streaming pipelines, and API endpoints for data access and integration.

REQUIREMENTS

• Experience on Python scripting, Spark SQL PySpark is a must
• Experience on ADLS, Azure Databricks, Azure SQL DB, EventHub, Kafka, 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
• Strong expertise in applying narrow and wide transformations to build efficient and scalable data pipelines in Databricks.