26 to 50 of 203 DataOps Jobs in England

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, and deployment problems. Implement data validation, monitoring, logging, and alerting. Work with development, analytics, and business teams to understand requirements. Follow DevOps and DataOps best practices around version control, automation, testing, and release management. Support continuous improvement of data platforms and reporting solutions. Mandatory: Strong hands-on Power … experience. Strong hands-on experience with native AWS services . Experience in Data Engineering/DataOps . Experience building ETL/ELT data pipelines . Experience with data modelling and data warehousing. Experience with CI/CD and DevOps practices . Experience with Git and source-code management. Strong troubleshooting ...

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 ...

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 ...

Snowpark, AWS Bedrock, SageMaker, vector search and semantic search architectures Experience delivering Business Intelligence platforms, self-service analytics solutions and working knowledge of DataOps, MLOps and LLMOps practices Demonstrable experience working in telecommunications and using industry best practice frameworks such as TM Forum, TOGAF, ITIL, BPMN and UML Life ...

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. ...

with multidisciplinary teams to deliver high-impact data solutions. You will code in Python and SQL, work with Snowflake and Azure Databricks, and apply DataOps principles to ensure data quality, governance, and scalable data products across client projects. #J-18808-Ljbffr ...

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 ...

Azure or GCP) and experience of associated technologies (for example with AWS: DynamoDB, Redshift, Kinesis Pipelines, Glue, Lambda, QuickSight, etc) Have experience with DataOps concepts Why join AND Digital? We have three core values: wonder, share, and delight. These values inform how we work with clients, and our culture: what ...

Azure or GCP) and experience of associated technologies (for example with AWS: DynamoDB, Redshift, Kinesis Pipelines, Glue, Lambda, QuickSight, etc) Have experience with DataOps concepts Why join our client? Were building a culture where talented people can do meaningful work, continue growing, AND enjoy the journey along the way. ...

Principal Data Engineer will establish engineering standards, shape platform strategy, mentor engineers and provide authoritative guidance on best practices across data architecture, platform design, DataOps, governance and cloud engineering. Your responsibilities will include... Act as the senior Azure Data Platform expert within the Data Engineering function, providing technical leadership, architectural … environments, driving adoption of cloud-native Azure services and best-practice engineering approaches Providing technical leadership, mentorship and guidance to Data Engineers while championing DataOps, DevOps, CI/CD and Infrastructure as Code practices to drive continuous improvement, platform optimisation and operational excellence What ...

Principal Data Engineer will establish engineering standards, shape platform strategy, mentor engineers and provide authoritative guidance on best practices across data architecture, platform design, DataOps, governance and cloud engineering. Your responsibilities will include... Act as the senior Azure Data Platform expert within the Data Engineering function, providing technical leadership, architectural … environments, driving adoption of cloud-native Azure services and best-practice engineering approaches Providing technical leadership, mentorship and guidance to Data Engineers while championing DataOps, DevOps, CI/CD and Infrastructure as Code practices to drive continuous improvement, platform optimisation and operational excellence What ...

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 ...

Azure or GCP) and experience of associated technologies (for example with AWS: DynamoDB, Redshift, Kinesis Pipelines, Glue, Lambda, QuickSight, etc) Have experience with DataOps concepts Equal Opportunities Statement Diversity and inclusion are hugely important to us, and we’re committed to providing equal opportunities for all. We’re actively recruiting ...

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 ...

modernising clients’ data estates and delivering scalable solutions across multiple cloud environments. You will work with Data Scientists, Platform Engineers, and business stakeholders, applying DataOps, CI/CD, and best practices, while mentoring engineers and #J-18808-Ljbffr ...

Dataflow, Pub/Sub, Cloud Interconnect, and Apigee. Experience with Infrastructure as Code (e.g., Terraform) and CI/CD principles in a data context (DataOps). Strong leadership and communication skills, with the ability to influence senior technical stakeholders and mentor other engineers. If you're excited about this role ...

documentation approaches that improve quality, maintainability, consistency and knowledge sharing across the Analytics Engineering function. Automation and AnalyticsOps Lead the adoption of automation and DataOps practices that improve the deployment, testing, monitoring and operational management of data products, enhancing scalability, reliability and developer productivity. AI and Analytics Enablement Shape … best practices, including coding standards, code reviews, testing strategies, version control systems such as Git, and CI/CD processes. Experience driving automation and DataOps practices that improve deployment, monitoring, reliability and operational efficiency of data products. Experience developing dashboards, visualisations and self-service analytics capabilities using tools such ...

Description The Role We are seeking a capable Consulting Data Architect to join our Insurance Technology Consulting practice and play a pivotal role in shaping, selling, and delivering data-led consulting engagements for insurance clients. ...

Are you passionate about building trusted customer data foundations that power meaningful marketing decisions? Would you like to shape scalable data pipelines and models that improve customer journeys, analytics, and business outcomes? LexisNexis Risk Solutions ...

organisation, aligning cloud-native data solutions with regulatory compliance and analytics needs. You will establish standards, mentor engineers, and promote best practices in DataOps, CI/CD, and Infrastructure as Code, while partnering with the Head of Data Engineering to deliver the #J-18808-Ljbffr ...