176 to 200 of 714 Databricks Jobs

frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services). Ability to handle, process, and analyse large, complex datasets. Strong understanding of data ethics, governance, and responsible AI principles. Must have SC Clearance and More ❯

frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services). Ability to handle, process, and analyse large, complex datasets. Strong understanding of data ethics, governance, and responsible AI principles. Must have SC Clearance and 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 ❯

sales teams in defining technical strategies, solution proposals, pricing, and bid responses. Hands-On Expertise: Provide technical guidance on Azure components such as Synapse Analytics, Data Factory, Data Lake, Databricks, Purview, Azure SQL, and Storage. What We're Looking For We're seeking someone who combines deep technical capability with strong consulting and leadership skills. You'll ideally have: Azure More ❯

formulate/execute a sales strategy to exceed revenue objectives Working on Microsoft Azure PaaS and IaaS, specifically: App Services, Azure SQL Database, SQL Server, Storage, Synapse Analytics, Purview, Databricks, Azure data Factory, Azure data lake. Understand which Azure data focused components to use for which purpose Your Skills and Experience Our projects are varied, sometimes you may be asked More ❯

formulate/execute a sales strategy to exceed revenue objectives Working on Microsoft Azure PaaS and IaaS, specifically: App Services, Azure SQL Database, SQL Server, Storage, Synapse Analytics, Purview, Databricks, Azure data Factory, Azure data lake. Understand which Azure data focused components to use for which purpose Your Skills and Experience Our projects are varied, sometimes you may be asked More ❯

Research Teams – Translate experimental findings into production-grade systems that extend the autonomy and reliability of agents. Run Experiments End-to-End – Own your compute environment (e.g. Jupyter, Colab, Databricks) and iterate on large-scale LLM training and evaluation. What You’ll Bring: 4+ years’ experience in Machine Learning or AI , with exposure to LLM agent systems , tool-use frameworks More ❯

Research Teams – Translate experimental findings into production-grade systems that extend the autonomy and reliability of agents. Run Experiments End-to-End – Own your compute environment (e.g. Jupyter, Colab, Databricks) and iterate on large-scale LLM training and evaluation. What You’ll Bring: 4+ years’ experience in Machine Learning or AI , with exposure to LLM agent systems , tool-use frameworks 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 ❯

Operations, or Digital Experience). Strong SQL skills for data extraction, transformation, and pipeline development. Proficiency in Tableau, Qlik, or similar visualization tools. Experience with big data tools (Snowflake, Databricks, Spark) and ETL processes. Exposure to Python or R for automation, experimentation, or analytics. Excellent communication and storytelling skills with both technical and non-technical audiences. Proactive, growth-oriented mindset More ❯

Operations, or Digital Experience). Strong SQL skills for data extraction, transformation, and pipeline development. Proficiency in Tableau, Qlik, or similar visualization tools. Experience with big data tools (Snowflake, Databricks, Spark) and ETL processes. Exposure to Python or R for automation, experimentation, or analytics. Excellent communication and storytelling skills with both technical and non-technical audiences. Proactive, growth-oriented mindset More ❯

PyTorch, TensorFlow, FastAI, and experience with scikit-learn, MLflow, or ONNX. Solid engineering background—experienced in deploying and maintaining ML systems on Azure, including Azure Machine Learning, Azure Functions, Databricks, Docker, and Kubernetes. Experience with real-time data pipelines and streaming data using tools such as Kafka or Azure Event Hubs is a plus. Advanced degree (Master’s or PhD More ❯

PyTorch, TensorFlow, FastAI, and experience with scikit-learn, MLflow, or ONNX. Solid engineering background—experienced in deploying and maintaining ML systems on Azure, including Azure Machine Learning, Azure Functions, Databricks, Docker, and Kubernetes. Experience with real-time data pipelines and streaming data using tools such as Kafka or Azure Event Hubs is a plus. Advanced degree (Master’s or PhD More ❯

project requirements with stakeholders. Qualifications At least 5 years of experience in a technical data role (data engineer, ML engineer, or data scientist). Hands on expertise with Azure, Databricks, and Snowflake. Strong command of Python and SQL. Experience managing multi disciplinary data teams. Solid understanding of data management concepts, including schema evolution and storage formats. Proficiency in software engineering More ❯

end ML lifecycle. - TECH STACK: Proficiency in Python (Pandas, NumPy, LangChain). Deep familiarity with the [Specific Vendor]’s [Cloud Environment] AI and Data Stack (Azure ML, Azure OpenAI, Databricks). - SPECIALIZATION: Expertise in Vector databases (FAISS, Pinecone, Azure AI Search), Prompt Engineering, and familiarity with products like [Specific Vendor Product 1]. THE CULTURE Our client seeks curious, pragmatic More ❯

with diverse audiences—from technical architects to CDOs. Deep Technical Expertise Across Data & AI: You possess comprehensive technical knowledge spanning the entire Data & AI landscape, including cloud platforms (Azure, Databricks, Snowflake, AWS &GCP). Knowledge of AI/ML, Gen AI and Agentic AI capabilities: You understand not just the "what" but the "how" and "why" behind these technologies, enabling More ❯

Python and SQL fundamentals The ability to get to grips with new technologies quickly Nice to Have: Experience in dashboarding tools, Typescript and API development Familiarity with Airflow, DBT, Databricks Experience working with Enterprise Resource Planning (e.g. Oracle, SAP) and CRM systems Compensation: Competitive salary - plus benefits package, annual bonus and stock options If you’re excited by everything you 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 ❯

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 ❯

products. Deep understanding of cloud computing, infrastructure-as-code, DevOps tooling , and data/AI platforms. Hands-on experience with one or more of: AWS, Azure, GCP, Kubernetes, Terraform, Databricks, or Vertex AI . Proven ability to collaborate with engineering and research teams to align platform capabilities with end-user needs. Skilled in stakeholder management and influencing at C-suite More ❯

products. Deep understanding of cloud computing, infrastructure-as-code, DevOps tooling , and data/AI platforms. Hands-on experience with one or more of: AWS, Azure, GCP, Kubernetes, Terraform, Databricks, or Vertex AI . Proven ability to collaborate with engineering and research teams to align platform capabilities with end-user needs. Skilled in stakeholder management and influencing at C-suite More ❯

products. Deep understanding of cloud computing, infrastructure-as-code, DevOps tooling , and data/AI platforms. Hands-on experience with one or more of: AWS, Azure, GCP, Kubernetes, Terraform, Databricks, or Vertex AI . Proven ability to collaborate with engineering and research teams to align platform capabilities with end-user needs. Skilled in stakeholder management and influencing at C-suite More ❯