101 to 125 of 592 Databricks Jobs in the UK

popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/ More ❯

track record building and maintaining scalable data platforms in production, enabling advanced users such as ML and analytics engineers. Hands-on experience with modern data stack tools - Airflow, DBT, Databricks, and data catalogue/observability solutions like Monte Carlo, Atlan, or DataHub. Solid understanding of cloud environments (AWS or GCP), including IAM, S3, ECS, RDS, or equivalent services. Experience implementing More ❯

lead Agile teams to deliver robust outcomes. Experienced in securing work through RFI/RFPs, bids, and presentations across public and private sectors. Skilled in data science platforms (e.g. Databricks, AzureML) and cloud services (AWS, Azure, GCP), with knowledge of tools like Terraform. Experienced in deploying solutions using Docker, Kubernetes, CI/CD tools. To be Considered: Please either apply More ❯

lead Agile teams to deliver robust outcomes. Experienced in securing work through RFI/RFPs, bids, and presentations across public and private sectors. Skilled in data science platforms (e.g. Databricks, AzureML) and cloud services (AWS, Azure, GCP), with knowledge of tools like Terraform. Experienced in deploying solutions using Docker, Kubernetes, CI/CD tools. To be Considered: Please either apply More ❯

Requirements Proven experience leading teams of engineers in delivering data-intensive system components. Proficient in Java, Scala, or Python . Hands-on experience with data-processing platforms (Informatica, Azure Databricks, or equivalent ETL tools). Expertise in SQL and analytical extensions . Strong understanding of distributed data stores and processing frameworks . Skilled in designing analytical and operational data models More ❯

principal capacity. Proven experience designing and governing complex, multi-cloud or hybrid solutions. Deep technical expertise in cloud, data, integration, and security architecture. Strong understanding of enterprise data platforms (Databricks, S3, Redshift), integration patterns (API Gateway, AppFlow, Logic Apps), and cloud-native services. Demonstrable leadership in delivering large-scale transformation or digital programmes. Proficiency in DevOps tooling (Terraform, GitHub, CodePipeline More ❯

principal capacity. Proven experience designing and governing complex, multi-cloud or hybrid solutions. Deep technical expertise in cloud, data, integration, and security architecture. Strong understanding of enterprise data platforms (Databricks, S3, Redshift), integration patterns (API Gateway, AppFlow, Logic Apps), and cloud-native services. Demonstrable leadership in delivering large-scale transformation or digital programmes. Proficiency in DevOps tooling (Terraform, GitHub, CodePipeline More ❯

principal capacity. Proven experience designing and governing complex, multi-cloud or hybrid solutions. Deep technical expertise in cloud, data, integration, and security architecture. Strong understanding of enterprise data platforms (Databricks, S3, Redshift), integration patterns (API Gateway, AppFlow, Logic Apps), and cloud-native services. Demonstrable leadership in delivering large-scale transformation or digital programmes. Proficiency in DevOps tooling (Terraform, GitHub, CodePipeline More ❯

principal capacity. Proven experience designing and governing complex, multi-cloud or hybrid solutions. Deep technical expertise in cloud, data, integration, and security architecture. Strong understanding of enterprise data platforms (Databricks, S3, Redshift), integration patterns (API Gateway, AppFlow, Logic Apps), and cloud-native services. Demonstrable leadership in delivering large-scale transformation or digital programmes. Proficiency in DevOps tooling (Terraform, GitHub, CodePipeline More ❯

analytical background, including experience with ESRI ArcGIS, Power BI, and FME, Excel. Knowledge of wastewater industry, capability in additional geospatial tools, analytical tools and data management (e.g. Python, SQL, Databricks, Azure Data Factory) will be beneficial. Proven ability to produce detailed management reports. High attention to detail with the ability to understand the wider business context. Strong communication skills and More ❯

running cost-effective serverless architecture. Experience working with Python, C#, and Angular. Strong interpersonal, communication, and presentation skills applicable to a wide audience. Experience with PyTorch, Scikit-learn, Go, Databricks, JavaScript, and Azure Pipelines is desirable, but not essential. Experience in leading software engineering efforts for AI-enabled SaaS products is desirable, but not essential. Why Join Us? Join our More ❯

drive to take ownership of tasks Tech Stack Core : Python, FastAPI, asyncio, Airflow, Luigi, PySpark, Docker, LangGraph Data Stores : Vector Databases, DynamoDB, AWS S3, AWS RDS Cloud & MLOps : AWS, Databricks, Ray ️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year Fully remote team - choose where you live ️ Work from home stipend! We More ❯

Experience domains. Proficiency in SQL for data extraction, transformation, and pipeline development. Experience with dashboarding and visualization tools (Tableau, Qlik, or similar). Familiarity with big data tools (Snowflake, Databricks, Spark) and ETL processes. Useful experience; Python or R for advanced analytics, automation, or experimentation support. Knowledge of statistical methods and experimentation (A/B testing) preferred. Machine learning and More ❯

to enhance reporting, analytics, and business intelligence solutions. What You Bring: 5+ years of experience in SQL production environments and data engineering. Strong expertise in SQL, T-SQL, Azure, DataBricks, and SSIS. Experience with data integration, modeling, and performance optimization. Problem-solving mindset and a collaborative approach. Desirable: Experience handling data from APIs and secure protocols. Familiarity with visualization tools More ❯

in implementing end-to-end ML pipelines (data, training, validation, serving) Experience with ML workflow orchestration tools (e.g., Airflow, Prefect, Kubeflow) and ML feature or data platforms (e.g., Tecton, Databricks, etc.) Experience with cloud platforms (AWS, GCP/Vertex, Azure), Docker, and Kubernetes Solid coding practices (Git, automated testing, CI/CD). Proficiency with Linux Familiarity with time-series More ❯

Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/data platforms (Databricks, Tecton, etc.). Strong experience with cloud platforms (AWS, GCP, or Azure), Docker, and Kubernetes. Solid coding practices, including Git, automated testing, and CI/CD. Proficiency with Linux environments. More ❯

Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/data platforms (Databricks, Tecton, etc.). Strong experience with cloud platforms (AWS, GCP, or Azure), Docker, and Kubernetes. Solid coding practices, including Git, automated testing, and CI/CD. Proficiency with Linux environments. More ❯

top-tier consultancy or blue-chip corporate. Demonstrable experience leading AI value delivery, CoE mobilisation, or multi-disciplinary product teams. Technical literacy across data and AI ecosystems (Azure, GCP, Databricks, Snowflake, Power BI, Kafka, LLMs). Exceptional stakeholder management up to CIO/CDO level with a track record of influence and measurable delivery. Strong grasp of responsible-AI, governance More ❯

top-tier consultancy or blue-chip corporate. Demonstrable experience leading AI value delivery, CoE mobilisation, or multi-disciplinary product teams. Technical literacy across data and AI ecosystems (Azure, GCP, Databricks, Snowflake, Power BI, Kafka, LLMs). Exceptional stakeholder management up to CIO/CDO level with a track record of influence and measurable delivery. Strong grasp of responsible-AI, governance More ❯

into a management (mentoring, coaching, team development etc) Very strong technical skills that will include - SQL, SSIS, SSRS, SAS, Power BI, Power Platform, Azure Data Factory, Azure Data Lake, Databricks A good understanding of dimensional modelling techniques, including Kimball's Business Development Lifecycle Ability to design hybrid data solutions across on-prem and cloud data sources Expert with data engineering More ❯

DATA HEAVY Product Owners who have managed complex, Global products. Read on for more details Experience required: Technical proficiency:Familiarity with Azure services (e.g., Data Lake, Synapse, Fabric) and Databricks for data engineering, analytics, performance optimisation, and governance. Experience with implementing and optimising scalable cloud infrastructure is highly valued. Backlog management:Demonstrated expertise in maintaining and prioritizing product backlogs, writing More ❯

DATA HEAVY Product Owners who have managed complex, Global products. Read on for more details... Experience required: Technical proficiency: Familiarity with Azure services (e.g., Data Lake, Synapse, Fabric) and Databricks for data engineering, analytics, performance optimisation, and governance. Experience with implementing and optimising scalable cloud infrastructure is highly valued. Backlog management: Demonstrated expertise in maintaining and prioritizing product backlogs, writing More ❯

into a management (mentoring, coaching, team development etc) Very strong technical skills that will include - SQL, SSIS, SSRS, SAS, Power BI, Power Platform, Azure Data Factory, Azure Data Lake, Databricks A good understanding of dimensional modelling techniques, including Kimball's Business Development Lifecycle Ability to design hybrid data solutions across on-prem and cloud data sources Expert with data engineering More ❯

background in data visualisation (Power BI/Looker/Looker Studio). Experience with regulated data environments and a disciplined approach to quality and documentation. Desirable: BigQuery, Snowflake, or Databricks; reverse-ETL tools; marketing attribution methods. Next Steps If you're a data scientist passionate about using data and making an impact, we would love to hear from you. Apply More ❯

across data modelling, integration, governance, and transformation. Experience with AWS (S3, Glue, Redshift, Lambda, Kinesis) and/or Azure (ADF, Synapse, Fabric). Familiarity with modern data platforms (e.g. Databricks, Snowflake, or Lakehouse environments). Ability to operate confidently in highly secure, mission-focused settings. Why Join? Work on meaningful security projects with real-world impact. Join a culture built More ❯