1 to 25 of 355 Permanent DataOps Jobs in the UK excluding London

offering guidance on how one would implement a robust DevOps approach in a data project. You can comfortably talk about tools needed such as DataOps in areas such as orchestration, data integration and data analytics. Desirable experience Experience in the following things isn't essential, but it's highly desirable ...

provide guidance how one would implement a robust DevOps approach in a data project. Also would be able to talk about tools needed for DataOps in areas such as orchestration, data integration and data analytics. Experience in improving resilience into a project by checking for software vulnerabilities and implement appropriate ...

provide guidance how one would implement a robust DevOps approach in a data project. Also would be able to talk about tools needed for DataOps in areas such as orchestration, data integration and data analytics. Experience in improving resilience into a project by checking for software vulnerabilities and implement appropriate ...

provide guidance how one would implement a robust DevOps approach in a data project. Also would be able to talk about tools needed for DataOps in areas such as orchestration, data integration and data analytics. Experience in improving resilience into a project by checking for software vulnerabilities and implement appropriate ...

provide guidance how one would implement a robust DevOps approach in a data project. Also would be able to talk about tools needed for DataOps in areas such as orchestration, data integration and data analytics. Experience in improving resilience into a project by checking for software vulnerabilities and implement appropriate ...

data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices (e.g. Terraform) and testing data pipelines, including end-to-end, data quality, monitoring, unit and contract testing. Experience managing the full data ...

data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices (e.g. Terraform) and testing data pipelines, including end-to-end, data quality, monitoring, unit and contract testing. Experience managing the full data ...

data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices (e.g. Terraform) and testing data pipelines, including end-to-end, data quality, monitoring, unit and contract testing. Experience managing the full data ...

enhance operational efficiency through innovative solutions. Nice to Have : Background in software delivery, with a solid grasp of CI/CD pipelines and DataOps methodologies. Exposure to ML/AI implementations. 3. Process & Delivery Management Operational Excellence : Manage delivery timelines, performance metrics, and team operations effectively. Support technology upgrades, evaluate ...

optimise scalable biological data processing pipelines (Nextflow, Seqera). Maintain and develop cloud-based infrastructure with high uptime, failsafes, and modern DevOps/DataOps practices. Implement data modelling solutions across relational and non-relational databases (PostgreSQL, Elasticsearch). ABOUT YOU You’ll thrive in this role if you have: Industry ...

role in shaping a modern Data Operations function as part of a major transformation. Stay hands-on while developing leadership skills in a true DataOps environment. Enjoy a balanced hybrid model - two days per week in your local office (Liverpool or Glasgow) plus fully expensed travel between sites when needed. ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...

problems Data quality and master data management — creating trusted, reliable data foundations Data governance — implementing frameworks that balance control with enablement Data architecture or DataOps — designing systems that scale AI/ML governance — managing risk while enabling innovation You've probably: Led or significantly contributed to data initiatives in complex ...