Proven track record of leadership of teams and problem solving at the enterprise scale in the field of Data Architecture, Science or Analytics. With hands-on technical delivery of client-facing data projects across the full SDLC from design to migration, integration and live service in a multi-vendor environment
Strong skills in languages such as Python, R, SQL or Scala, alongside experience of using modern and traditional data technologies including: ElasticSearch, MongoDB, PostgreSQL, mySQL/mariaDB, Oracle, SQL Server, Hadoop, Kafka, Splunk/ELK or other logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies. This should be backed with strong cloud-native data engineering skills e.g. AWS RDS, Aurora, Redshift, Kinesis, Glue or Azure CosmosDB, DataFactory, DataWarehouse, SQL DB etc.
Proven experience in quality assuring data programmes, including non-functional testing and performance tuning
Hands-on experience of modern software delivery, including CI/CD and DevOps practices with a deep understanding and extensive track record of delivering complex data solutions using Agile methods including Scrum, SAFe etc.
A keen understanding of industry best-practice around standards, quality and continuous improvement in the field of Data Engineering
Experience in conducting large scale enterprise batch and real-time processing from varying sources
Experience in building and designing scalable and extensible enterprise data architectures
Requirements
Proven track record of leadership of teams and problem solving at the enterprise scale in the field of Data Architecture, Science or Analytics. With hands-on technical delivery of client-facing data projects across the full SDLC from design to migration, integration and live service in a multi-vendor environment
Strong skills in languages such as Python, R, SQL or Scala, alongside experience of using modern and traditional data technologies including: ElasticSearch, MongoDB, PostgreSQL, mySQL/mariaDB, Oracle, SQL Server, Hadoop, Kafka, Splunk/ELK or other logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies. This should be backed with strong cloud-native data engineering skills e.g. AWS RDS, Aurora, Redshift, Kinesis, Glue or Azure CosmosDB, DataFactory, DataWarehouse, SQL DB etc.
Proven experience in quality assuring data programmes, including non-functional testing and performance tuning
Hands-on experience of modern software delivery, including CI/CD and DevOps practices with a deep understanding and extensive track record of delivering complex data solutions using Agile methods including Scrum, SAFe etc.
A keen understanding of industry best-practice around standards, quality and continuous improvement in the field of Data Engineering
Experience in conducting large scale enterprise batch and real-time processing from varying sources
Experience in building and designing scalable and extensible enterprise data architectures
Benefits
25 days holiday allowance + bank holidays
Share scheme
A £1000 flexifund to use on a personalised list of benefits such Gym membership, Cycle to Work Scheme, Health, dental and optical cash plan
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