1 to 25 of 131 DataOps Jobs in the UK

/CD tools (Jenkins, GitHub Actions), infrastructure-as-code (Terraform, CloudFormation). Industry Standards:ISA-95, Unified Namespace (UNS), FAIR data principles, and DataOps methodologies. ...

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 ...

analytics and engineering Strong understanding of various architectures including data warehouses, data lakes, data lake houses and data mesh Strong understanding of best practice DataOps and MLOps Up-to-date understanding of various data engineering technologies including Apache Spark, Databricks and Hadoop Strong understanding of agile ways of working ...

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 ...

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 ...

trading, quantitative research environments or other data-intensive industries. Exposure to real-time analytics, monitoring, and observability tools (Grafana, Prometheus, DataDog etc.) Understanding of DataOps, FinOps, and cost-optimised data management practices. Familiarity with distributed systems and high-throughput data processing (e.g. Ray, Dask, Spark). Experience with feature engineering ...

Role Type: Contracting Mode of Working: 100% office Key Skills/Knowledge/Experience Required: Proven experience as a DevOps Engineer, Cloud Engineer, or DataOps Engineer working in Azure-based data platforms, supporting complex, large-scale workloads within mature Agile delivery environments. Deep hands-on expertise with Azure Databricks, including ...

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 ...