1 to 25 of 99 Permanent Databricks Jobs in Central London

CDO level and translating requirements into solution blueprints, proposals, and presentations. Enterprise Solution Design – Architect end-to-end data and cloud solutions across platforms such as Azure, AWS, GCP, Databricks, Snowflake, Synapse, or Azure Fabric. Cloud Strategy & Adoption – Define and lead cloud migration, modernisation, and optimisation strategies using tools such as Terraform, Azure DevOps, and CI/CD pipelines. Data More ❯

viable and technically sound solutions. Enterprise Solution Design Architect and oversee the delivery of scalable data platforms (data lakes, lakehouses, warehouses) using GCP technologies such as BigQuery, Cloud Storage, Databricks, and Snowflake. Cloud Data Strategy Lead cloud migration and modernisation strategies using GCP and tools like Terraform, CI/CD pipelines, Azure DevOps, and GitHub. Data Modelling Apply hands-on More ❯

data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications Experience with Databricks or Ray. Familiarity with dbt and Airflow. Experience with data quality frameworks. Understanding of ML requirements and experience working with ML teams. Experience in robotics or a related field. Familiarity More ❯

data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications Experience with Databricks or Ray. Familiarity with dbt and Airflow. Experience with data quality frameworks. Understanding of ML requirements and experience working with ML teams. Experience in robotics or a related field. Familiarity More ❯

development experience with: C# (.NET/.NET Core) REST APIs, SQL Server (T-SQL), HTML/CSS/JavaScript/React, Python Comfortable with tools like Azure Data Factory , Databricks , Power Automate , Power Platform , Copilot Studio . Strong knowledge of cloud security , automation , and DevOps principles. ?? Bonus Points for: Experience in the insurance market Familiarity with data architecture and data More ❯

solution strategies, guiding delivery teams, and acting as a trusted advisor to CDOs, CIOs, and Heads of Data. 🔑 What You’ll Do Lead enterprise solution design on GCP, BigQuery, Databricks, Snowflake Drive cloud migration & modernisation strategies (Terraform, CI/CD, Azure DevOps, GitHub) Define enterprise data models (ERwin, ER/Studio, PowerDesigner) Architect ETL/ELT frameworks & pipelines (Dataflow, Dataproc More ❯

Python and SQL. Experience with data integration tools and technologies (e.g. DLT, Meltano, APIs, Kafka). Knowledge of cloud platforms such as AWS. Familiarity with modern data platforms (e.g. Databricks, Snowflake, or BigQuery). Strong communication and collaboration skills. Proven experience in data engineering or data platform development. BENEFITS Private Medical Care: Access to premium healthcare facilities and professionals. Health More ❯

Python and SQL. Experience with data integration tools and technologies (e.g. DLT, Meltano, APIs, Kafka). Knowledge of cloud platforms such as AWS. Familiarity with modern data platforms (e.g. Databricks, Snowflake, or BigQuery). Strong communication and collaboration skills. Proven experience in data engineering or data platform development. BENEFITS Private Medical Care: Access to premium healthcare facilities and professionals. Health More ❯

model training and inference. Driving best practices in data governance, security, and performance optimisation. What We're Looking For Strong experience with Azure cloud services, especially Data Factory, Synapse, Databricks, and Azure Functions. Proficiency in Python, SQL, and data transformation techniques. Experience working with both structured and unstructured data sources. Understanding of AI/ML data requirements and how to More ❯

market, credit, and operational risk, compliance, and trade lifecycle Proven in delivering complex risk and compliance solutions Strong leadership and stakeholder management skills Bonus: Python, Azure Data Factory/Databricks, data analysis, and COTS risk platforms (e.g., CubeLogic, deltaconX) Package 85,000 Base Salary 15% non-contributory pension Hybrid working (3 days per week) Performance-based bonus scheme Comprehensive benefits More ❯

What You’ll Bring Must-Have Skills 5+ years in Sales Ops/Rev Ops roles Proficient in SQL and Python (Pandas, PySpark) Strong experience with cloud data platforms (Databricks, Snowflake, GCP) Background in building ETL/ELT solutions and data modelling Advanced Excel/Power BI/VBA skills 2+ years’ experience with Salesforce (essential) Preferred Skills Experience launching More ❯

skills You're comfortable taking ownership of projects and working end-to-end You have a good knowledge of Distributed Systems and DevOps tooling Ideally you will also have Databricks experience What's in it for you: As a Senior Data Engineer you will earn a highly competitive package: Salary to £85k Bonus c15% Pension (up to 7% employer contribution More ❯

Communicating data-driven insights and influencing both technical and business stakeholders What We’re Looking For Expert-level Python (scikit-learn, pandas, etc.), SQL, and big data platforms (e.g. Databricks) Proven experience with MLOps : deploying, monitoring, and scaling models in production Strong cloud experience (AWS, GCP, or Azure) and comfort with CI/CD pipelines Broad data science expertise spanning More ❯

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 ❯

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 ❯

Core AI Expertise Deep understanding of AI solutions, frameworks, and security, with the ability to apply them to real business challenges. Expertise in cloud data platforms and architecture (e.g. Databricks, Snowflake, Azure, AWS). Awareness of emerging technologies, regulatory trends, and developments in areas such as Agentic AI. Strong capability across key data domains including Data & AI Governance, Data Quality More ❯

Core AI Expertise Deep understanding of AI solutions, frameworks, and security, with the ability to apply them to real business challenges. Expertise in cloud data platforms and architecture (e.g. Databricks, Snowflake, Azure, AWS). Awareness of emerging technologies, regulatory trends, and developments in areas such as Agentic AI. Strong capability across key data domains including Data & AI Governance, Data Quality 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 ❯

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 ❯

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 ❯

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 ❯

Job Summary : We are seeking a highly skilled and experienced Senior Data Engineer to join our team and contribute to the development and maintenance of our cutting-edge Azure Databricks platform for economic data. This platform is critical for our Monetary Analysis, Forecasting, and Modelling activities. The Senior Data Engineer will be responsible for building and optimising data pipelines, implementing … Development & Optimisation : Design, develop, and maintain robust and scalable data pipelines for ingesting, transforming, and loading data from various sources (e.g., APIs, databases, financial data providers) into the Azure Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark … or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and More ❯

Job Summary : We are seeking a highly skilled and experienced Senior Data Engineer to join our team and contribute to the development and maintenance of our cutting-edge Azure Databricks platform for economic data. This platform is critical for our Monetary Analysis, Forecasting, and Modelling activities. The Senior Data Engineer will be responsible for building and optimising data pipelines, implementing … Development & Optimisation: Design, develop, and maintain robust and scalable data pipelines for ingesting, transforming, and loading data from various sources (e.g., APIs, databases, financial data providers) into the Azure Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark … or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and More ❯

leadership Hands-on background in model deployment Strong B2C experience (e.g. ecommerce, gaming, telco) MSc required; PhD optional Executive-level stakeholder management Exposure to GenAI and cloud ML stacks (Databricks, Azure, AWS) Pathway to Chief Data Officer Interested? Please apply below. More ❯

relationships. Key Skills & Experience: Proven experience as a Platform Technical Lead, Data Architect, or similar role, leading enterprise data platforms at scale. Strong technical expertise in Azure, AWS, Snowflake, Databricks, Data Lakes, and Kafka. Deep understanding of modern data platform architectures, including Lakehouse, Kappa, and Lambda. Experience designing and managing secure, scalable, and governed data platforms. Strong knowledge of Data More ❯