Databricks Engineer

• Designing and implementing

   highly performant metadata driven data ingestion & transformation pipelines from multiple sources

  using Databricks and Spark

• Streaming and Batch processes in Databricks

• SPARK performance\tuning\optimisation

• Providing technical guidance for complex geospatial problems and spark dataframes

• Developing scalable and re-usable frameworks for ingestion and transformation of large data sets
• Data quality system and process design and implementation.
• 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 other members of the project team to support delivery of additional project components (Reporting tools, API interfaces, Search)
• Evaluating the performance and applicability of multiple tools against customer requirements

Working within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints.

Qualifications

• Direct experience of building data piplines using Azure Data Factory and Databricks

• Experience Required is 6 to 8 years

• Building data integration with Python
• Databrick Engineer certification
• Microsoft Azure Data Engineer certification.
• Hands on experience designing and delivering solutions using the Azure Data Analytics platform.
• Experience building data warehouse solutions using ETL / ELT tools like Informatica, Talend.
• Comprehensive understanding of data management best practices including demonstrated experience with data profiling, sourcing, and cleansing routines utilizing typical data quality functions involving standardization, transformation, rationalization, linking and matching.

Nice to have

• Experience working in a Dev/Ops environment with tools such as Microsoft Visual Studio Team Services, Chef, Puppet or Terraform
• Experience working with structured and unstructured data including imaging & geospatial data.
• Experience with Open Source non-relational / NoSQL data repositories (incl. MongoDB, Cassandra, Neo4J)
• Experience with Azure Event Hub, IOT Hub, Apache Kafka, Nifi for use with streaming data / event-based data.