1 to 25 of 39 Permanent Databricks Jobs in the City of London

relevant insights. * Experience working in regulated environments such as pensions, insurance, or financial services is highly advantageous. Desirable * Exposure to actuarial modelling or financial risk analysis. * Familiarity with Azure Databricks, Synapse, or distributed computing tools. * Experience applying model explainability and responsible AI techniques. Rewards & Benefits This role offers a comprehensive and flexible benefits package designed to support wellbeing and personal More ❯

performance data pipelines (ETL/ELT) to ingest, transform, and deliver data from diverse sources. Required Skills & Experience: Deep expertise in building and deploying data solutions using platforms like Databricks (Azure/AWS) , Microsoft Fabric , Azure Data Factory , and Azure Synapse . Solid experience with the Microsoft data stack —including SSIS , SSAS , and SSRS . A strong foundation in data More ❯

aimed at maximizing value through data utilization. Knowled g e/Experience Expertise in Commercial/Procurement Analytics. Experience in SAP (S/4 Hana). Experience with Spark, Databricks, or similar data processing tools. Stron g technical proficiency in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and More ❯

junior colleagues. You will bring experience in designing data solutions, writing code, and documentation, and must have strong skills in tools including but not limited to: MS Fabric stack Databricks Azure SQL Tableau/Power BI A knowledge of data modelling and of general IT architecture and systems integration is also required. Other technologies such as Azure Data Factory, RedShift More ❯

data platforms, especially Data Lakehouse, to enhance underwriting analytics and business insights. Key requirements Hands on experience designing and delivering solutions using Azure services including Azure Data Factory, Azure Databricks High proficiency in SQL and Python Insurance background If you are looking for a company who nurture and retain the best talent in the market then apply today. Interviews are More ❯

to high-impact solutions that support both internal teams and strategic initiatives. Your Experience Should Include: Strong experience in a data development and automation role Experience with Azure Synapse, Databricks, or Power Apps. Knowledge of DevOps practices and CI/CD pipelines in Azure. Why Join? Meaningful work: Build data solutions that support a healthcare mission with real-world impact. More ❯

proven commercial experience as a Data Scientist or ML Engineer Exposure to behavioral or consumer data is essential, preferably in the Healthcare space Strong Python skills and experience with Databricks or similar platforms Proven track record in predictive modelling with messy, real-world datasets (survey, geospatial, or similar) Hands-on experience with MLOps tools and practices (e.g., MLFlow) and deploying More ❯

complex delivery. Passionate about the real-world impact of AI and emerging technologies. Nice to Have Experience in sectors like telco, financial services, or retail. Knowledge of tools like Databricks, Snowflake, or Azure ML. Understanding of generative AI use cases and deployment frameworks. Why this opportunity? Work on complex, strategic programmes that blend consulting with hands-on innovation. Collaborate with More ❯

users in line with security standards Qualifications ✔ Experience in a data, operations, or analytics-focused role ✔ Familiarity with BI and reporting platforms such as Power BI, Datorama, Data Studio, Databricks, SQL ✔ Strong communication skills and a collaborative, solutions-focused mindset ✔ An organised, proactive approach—comfortable working across teams and timelines ✔ Excitement for new technology, data storytelling, and digital marketing innovation More ❯

segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge of media measurement techniques, such as media mix modelling. Experience More ❯

segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge of media measurement techniques, such as media mix modelling. Experience More ❯

chance to be involved in all aspects of the project process from conception through to completion and launch. Python Developer Experience: * Python, including APIs, data structures, and async processing * Databricks/Microsoft Fabric * Cloud, preferably Azure (Data Lake, Functions, App Services) * Containerisation with Docker and CI/CD pipelines * MLOps tooling (MLFlow, Git-based versioning, environment tracking) Desirable Skills & Interests More ❯

to translate data into action What You’ll Bring Strong hands-on data science and ML experience Expert in Python and modern data science libraries Experience with AWS SageMaker, Databricks, or similar cloud tools Strong background in supervised/unsupervised learning, statistical modelling, and model deployment Solid understanding of NLP techniques for document processing Domain experience in insurance (e.g., underwriting More ❯

the customer business. Able to understand the architecture on any Hyper-scaler [Azure and GCP] and identify potential opportunities for improvement. Knowledge of cutting edge data platforms such as Databricks & Snowflake Able to Create Business Plan for expanding business – Potential Business Opportunities/Competition Strengths, Weaknesses, Continuous improvement, Innovation, and growth Mindset Key Skills Strategic Thinking and Execution Deep E More ❯

also mentoring customers to foster self-sufficiency. Technical expertise will be essential in guiding customers through system and data architecture, integrating with cloud data warehouses such as Snowflake and Databricks; supporting the integration of external data sources, developing data models and ETL processes; to driving value through dashboards or business applications. Integrating AI tools and LLMs to unlock valuable insights … Translate key business requirements into effective solutions that drive customer value Guide customers on system and data architecture, including best practice integrations with CDW’s such as Snowflake and Databricks Oversee the full project lifecycle, from conception to delivery and sign-off, ensuring seamless collaboration with technical consultants, architects and customers Technical Problem Solving: Assist customers in resolving technical challenges … Deep understanding of at least one database technology (relational, columnar, or NoSQL) and familiarity with others (e.g., MySQL, Oracle, MSSQL, Vertica, MongoDB) Knowledge of cloud data warehouses like Snowflake, Databricks, and BigQuery Proven ability to manage technical project delivery, including scoping, planning, and risk assessment Strong organisational skills to oversee multiple concurrent customer projects Adaptability to shifting customer requirements and More ❯

also mentoring customers to foster self-sufficiency. Technical expertise will be essential in guiding customers through system and data architecture, integrating with cloud data warehouses such as Snowflake and Databricks; supporting the integration of external data sources, developing data models and ETL processes; to driving value through dashboards or business applications. Integrating AI tools and LLMs to unlock valuable insights … Translate key business requirements into effective solutions that drive customer value Guide customers on system and data architecture, including best practice integrations with CDW’s such as Snowflake and Databricks Oversee the full project lifecycle, from conception to delivery and sign-off, ensuring seamless collaboration with technical consultants, architects and customers Technical Problem Solving: Assist customers in resolving technical challenges … Deep understanding of at least one database technology (relational, columnar, or NoSQL) and familiarity with others (e.g., MySQL, Oracle, MSSQL, Vertica, MongoDB) Knowledge of cloud data warehouses like Snowflake, Databricks, and BigQuery Proven ability to manage technical project delivery, including scoping, planning, and risk assessment Strong organisational skills to oversee multiple concurrent customer projects Adaptability to shifting customer requirements and More ❯

critical decisions. What You’ll Do Lead the development and deployment of advanced analytics, data science, and machine learning tools and solutions. Use technologies such as Python, R, Azure, Databricks, SQL, Power BI, and Tableau to deliver actionable insights from complex data. Guide and mentor junior data scientists and analysts, fostering a culture of growth and technical excellence. Collaborate with … Desirable Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of More ❯

Requirements • Core DevOps skills - IaC - CI/CD pipelines - Team City, Jenkins, GitLab, Terraform • Core Azure skills - PaaS, Azure DevOps, Vault, (AKS nice to have) • Microsoft Azure cloud platform • Databricks, Azure Data Factory knowledge. More ❯

process: 3 stages 📢 Reporting to: Head of Data 👏 Company size: ~300 🎯 Working on: data warehousing, transformation, modelling & visualisation What are we looking for? Hands-on experience with SQL, dbt, Databricks, PowerBI (or similar) & broader modern data tools A strong technical track record of building robust data solutions The ability to communicate data impact clearly & engage business decision makers The ability More ❯

Skills: Strong understanding of asset management and data challenges faced Strong leadership skills with experience managing, mentoring, and developing high-caliber analytics teams Familiarity with analytics tools such as Databricks and PowerBI Experience with AI and automation Strong stakeholder management and communications skills Strategic mindset with the ability to translate complex data into clear, actionable business insights Please note that More ❯

Data & ML Product Lead: 5+ years experience in Data product management with a background delivering data products Experience managing and establishing governance Strong understanding of Azure products such as Databricks Good background in Machine Learning (ML) analytics and deploying products Proven ability to mentor teams and lead continuous improvement in the data environment Excellent communication skills, attention to detail and More ❯

Azure Functions is a plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Required Skills Exceptional collaboration and relationship building skills Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces Resilient problem solving and critical More ❯

ability to engage technical and non-technical stakeholders alike. The Head of Data Engineering & Insight will work within a modern, cloud-based BI ecosystem , including: Data Integration: Fivetran , HVR, Databricks , Apache Kafka, Google BigQuery , Google Analytics 4 Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST … API Advanced Analytics: Databricks (AI & Machine Learning) Governance & Infrastructure: Centralised Data Catalogue & Access Control (Okta) Job Scheduling & Monitoring (AWS, Splunk) Agile Data Engineering with centralised code repositories BI Data Portal: Power BI However this coexists with a legacy tech stack , which theHead of Data Engineering & Insight will support the transition to the new architecture already in place. Qualifications/Education More ❯

Azure Functions is a plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Exceptional collaboration and relationship building skills More ❯

to support experimentation and deployment. 🛠️ Key Responsibilities Build and maintain high-performance data pipelines to power AI/ML use cases Architect cloud-native data platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL/ELT workflows to support feature engineering, model training, and inference … Scala or Java Experience supporting AI/ML workflows and working with Data Scientists Exposure to cloud platforms: AWS , Azure , or GCP Hands-on with modern data tooling: Spark , Databricks , Snowflake , Airflow Solid grasp of data modelling, orchestration, and infrastructure-as-code (Terraform, Docker, CI/CD) Excellent communication and client-facing skills—comfortable leading on technical delivery 🎁 What’s More ❯