Data Engineer

Data Engineer Hybrid

3 days onsite Charlotte (locals only) 10+ months

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.