Data Engineer

Data Engineer
Hybrid - 3 days onsite Charlotte ( locals only)
10+ months


Internal notes: l6+ 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 dat
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 Jir
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.