Senior Data Engineer supporting AI - enabled financial compliance initiative with data pipelines and ingestion processes. Collaborating with diverse teams in a mission - critical regulated environment.
About the role
- Data Architect leading enterprise data projects with hands-on technical delivery and extensive data technologies experience. Join AND Digital to help close the digital skills gap.
Responsibilities
- 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
- 6% pension
- PLUS many more
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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