1 to 25 of 125 DataOps Jobs in London

data platforms support AI and machine learning, including feature data, retrieval and data preparation for generative AI. Experience of data observability and DataOps practices. Experience in a channel, reseller or technology partner environment Experience creating reusable offerings, reference architectures or assessments within a consulting or pre-sales practice. Experience mentoring ...

improvement points in individual components and the system as a whole, with a clear path to shaping platform-level decisions at Staff level. Embed DataOps best practices across the team: CI/CD, testing, observability, data drift monitoring, and incident response using tools like Grafana and Datadog. Collaborate with ...

lifecycle, including role- or attribute-based access, row or document-level permissions, masking or tokenisation, retention, tenant isolation and audit logging. Apply software and DataOps practices including Git, automated testing, CI/CD, infrastructure as code where relevant, performance tuning, cost optimisation and production support. Collaborate with finance SMEs, data ...

understanding of various data architectures, such as Lakes and Warehouses Knowledge of data cleansing and transformation within unified, standardised schemas Basic SQL DevOps and DataOps Awareness of IaC tools, particularly Terraform Knowledge of basic logging and monitoring practice Knowledge of basic access controls, policies and approaches particularly on Cloud services ...

Java ETL/ELT design and data pipeline orchestration Streaming and event-driven data architectures Agile and DevOps delivery methodologies applied to data platforms (DataOps) Expertise in data architecture and modelling (conceptual, logical, and physical) Familiarity with modern integration technologies and patterns (e.g., API-driven, event streaming, service mesh) Benefits ...

user stories into practical architectural designs that can be delivered by our Data Engineering team, whilst supporting our broader move towards a Dev/DataOps culture and a more product-led approach to data. About the team The Technology team provides expertise and effective solutions to Penguin Random House. ...

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. Experience in the following things isn’t essential, but it’s highly desirable! 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 ...

client deliverables. Communicating effectively with clients to discuss project progress and details as required. Being a key contributor in the implementation and maintenance of DataOps and governance policies, processes, and standards. Hands-on involvement in data integrations, warehousing, automation and related engineering tasks. Overseeing the deliveries across multiple clients ...

Model data structures, flows and architectures to support analytics and operational use cases Implement data storage solutions across cloud and on-prem environments Apply DataOps/software engineering best practices for deployment and reliability Ensure strong data governance, metadata management and security controls What theyre looking for Strong experience ...

data modelling, architecture, governance, quality and operational resilience Build data foundations capable of supporting AI, ML, vector search and advanced analytics Establish strong DataOps, CI/CD, observability and data quality practices Lead and develop a high-performing data engineering function Partner with Product, Engineering, Data Science and senior leadership ...

workflows to support operational requirements and analytics. Implement and maintain data storage solutions across cloud-based and on-premises environments. Apply software engineering and DataOps principles to improve deployment, automation, monitoring and reliability. Support data quality, governance, metadata management and security requirements. Collaborate with technical teams and stakeholders to deliver ...

engineers and contribute to team capability building. Technical Stack Core: SQL Server Databricks Infrastructure as Code (Terraform, Bicep) REST APIs GitHub Actions Microsoft Fabric DataOps practices What You'll Bring Solid understanding of data architecture, APIs, and modern data pipeline design. Strong experience within Microsoft's Azure ecosystem, combined with ...

customers. Support Proof of Concepts and pre-sales engagements with credible, hands-on technical depth. Establish best practices for governance, security, CI/CD, DataOps and MLOps. Collaborate closely with Databricks and internal delivery teams. Mentor engineers and help grow the consultancy's technical capability. What We're Looking ...

issues. Collaborate with client teams, architects, and internal stakeholders to translate business needs into technical solutions. Mentor engineers, contribute to technical standards, and promote DataOps and engineering best practices across the team. Communicate architecture decisions, progress, and analysis clearly to technical and non-technical audiences. Required Skills 7+ years …/CD tooling such as Jenkins, GitHub, or Cloud Build. Strong understanding of data security in regulated environments. Strong knowledge of DevOps/DataOps and Agile delivery practices. Excellent written and verbal communication skills. Strong analytical, debugging, and problem-solving skills. Nice to Have GCP Professional Data Engineer or Professional ...

location. Are you a technical leader who can turn data strategy into operational capability? We are looking for an exceptional Head of BI Platforms & DataOps to provide operational and technical leadership for the capability supporting analytics across South East and South West London.This is a senior technical, operational and people … establishing the platforms, engineering standards, operating practices, automation and service disciplines required to provide reliable, scalable and efficient analytical services.You will lead a modern DataOps capability that enables analysts and Data Scientists to work faster, more consistently and with greater confidence in the data, platforms and analytical products they use. ...

such as Flink, Kafka Streams and Kafka Connect Knowledge of modern data lake technologies including Delta Lake, Iceberg and Glue Data Catalog Exposure to DataOps practices and collaboration with Data Engineering teams Familiarity with GPU‐accelerated analytics using Spark with GPUs or RAPIDS Programming experience with Java, Scala, C#, Python ...

such as Flink, Kafka Streams and Kafka Connect Knowledge of modern data lake technologies including Delta Lake, Iceberg and Glue Data Catalog Exposure to DataOps practices and collaboration with Data Engineering teams Familiarity with GPU-accelerated analytics using Spark with GPUs or RAPIDS Programming experience with Java, Scala, C#, Python ...

understand business requirements and translate them into robust technical solutions. Contribute to solution architecture, platform design, and technology selection decisions. Implement software engineering and DataOps best practices including testing, observability, CI/CD, version control, and infrastructure automation. Develop and optimise data models, transformations, and storage layers to ensure performance … Apache Spark, Airflow, Dagster, Kafka, Flink, or equivalent tooling. Solid understanding of data lakehouse, warehouse, and medallion architecture patterns. Experience applying DevOps and DataOps best practices including CI/CD, automated testing, monitoring, observability, and release management. Experience with Infrastructure as Code technologies such as Terraform, Pulumi, CloudFormation, or Bicep. ...

stakeholder management skills. Desirable Experience Snowflake, cloud data warehousing and modern data platform delivery. AWS data services, cloud-native architecture and data pipeline orchestration. DataOps, automated deployment, Infrastructure as Code and release automation. Agile software development, code reviews, test-driven development and engineering quality assurance. AI-assisted software engineering, generative ...

cloud-based platforms. Define appropriate transition architectures and approaches that support successful implementation and ongoing operation. Engineering Standards & Optimisation Establish effective approaches to DataOps, CI/CD and infrastructure automation. Promote strong engineering standards, reusable implementation approaches and effective monitoring. Support the performance and cost optimisation of cloud data environments. … batch and real-time data pipelines. Experience designing appropriate data governance, security and data quality controls. Experience with modern engineering and deployment practices, including DataOps, CI/CD and infrastructure as code. Strong technical problem-solving skills and the ability to translate complex requirements into practical solutions. Experience leading complex ...

technical workshops, architecture reviews and discovery sessions. Support Proof of Concepts and pre-sales engagements. Establish best practices for governance, security, CI/CD, DataOps and MLOps. Collaborate closely with Databricks and internal delivery teams. Mentor engineers and help grow the consultancy's technical capability. What We're Looking ...

scale. You Might Be a Great Fit if You: Have experience at tech and product-driven companies, with a big focus on data quality, DataOps and data management at scale Have experience developing data warehouses/lakehouses Have used a variety of tools across the data stack and can select ...

such as Kafka, Debezium and CDC pipelines Desirable: experience with security and compliance in database environments, covering encryption, auditing and RBAC Desirable: familiarity with DataOps practices and collaboration with Data Engineering teams Benefits Highly competitive compensation plus annual discretionary bonus Lunch provided (via Just Eat for Business) and dedicated barista ...

driven, API, orchestration and ELT/ETL integration patterns using modern data integration technologies. Establish standards for analytics engineering, dbt, the modern data stack, DataOps, testing, documentation, CI/CD, Infrastructure as Code, observability and automated deployment. Embed metadata, lineage, privacy, security, regulatory compliance, monitoring and data quality controls into … requirements. Advanced experience with dbt and enterprise-scale modern data stack architectures, including framework design, governance, testing, documentation and deployment standards. Ability to establish DataOps practices that improve automation, quality and observability across data pipelines. Software Engineering & DevOps Strong software engineering background, with proficiency in Python and SQL and knowledge ...