151 to 175 of 1,065 Remote Databricks Jobs

business context Data wrangling, statistical analysis, machine learning, and predictive modeling Python and libraries such as Pandas, NumPy, Scikit-learn SQL, Power BI, and Databricks Strong business acumen: ability to translate data insights into business recommendations Cloud & GenAI Expertise: Hands-on with Azure cloud services (Azure ML, Azure AI, Azure More ❯

develop future contacts. Skills & Experiences Proven expertise in cloud platforms such as Azure, AWS, or Google Cloud. Knowledge of cloud-native data services (e.g., Databricks, Snowflake). Understanding of data modelling (relational, NoSQL) and ETL/ELT processes. Experience with data integration tools (e.g., Kafka, Talend) and APIs. Familiarity with More ❯

Computer Science, Mathematics, or a related field Familiarity with BI tools such as Looker for reporting and dashboarding Exposure to other environments such as Databricks, Snowflake, AWS, Azure, or DBT Understanding of observability, monitoring, and logging in GCP GCP Professional Data Engineer certification (or similar) What’s on Offer Competitive More ❯

Computer Science, Mathematics, or a related field Familiarity with BI tools such as Looker for reporting and dashboarding Exposure to other environments such as Databricks, Snowflake, AWS, Azure, or DBT Understanding of observability, monitoring, and logging in GCP GCP Professional Data Engineer certification (or similar) What’s on Offer Competitive More ❯

Computer Science, Mathematics, or a related field Familiarity with BI tools such as Looker for reporting and dashboarding Exposure to other environments such as Databricks, Snowflake, AWS, Azure, or DBT Understanding of observability, monitoring, and logging in GCP GCP Professional Data Engineer certification (or similar) What’s on Offer Competitive More ❯

with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL/ELT pipelines . Proficiency More ❯

Experiences Proven expertise in cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform. In-depth knowledge of cloud-native data services (e.g., Databricks, Snowflake, Microsoft Fabric, AWS Redshift). Strong understanding of data modelling (relational, dimensional, NoSQL) and ETL/ELT processes . Experience with data integration tools More ❯

in Python and SQL for data manipulation and model development. Experience in working with large-scale datasets and utilizing big data technologies (e.g., Azure, Databricks, Spark) Familiarity with data visualization tools such as Power BI, or matplotlib Strong knowledge of predictive modeling, machine learning techniques, and statistical analysis. Soft Skills More ❯

experience and ability to collaborate with data engineers to polish solutions for customer-readiness SQL Azure, Synapse Analytics (dataflows, Jupyter notebooks, on-demand SQL), Databricks, ADF Power BI, DAX, data flows SSIS Appreciation of information security standards such as ISO27001, PCI-DSS or Cyber Essentials BPSS clearance will be required More ❯

solutions align with NHS requirements and best practices. Develop end-to-end data solutions leveraging Azure services, including Azure Synapse Analytics, Azure Data Factory, Databricks, and Azure SQL. Define data models, integration patterns, and governance frameworks to ensure efficient data management, interoperability, and compliance. Drive cloud migration strategies for NHS More ❯

solutions align with NHS requirements and best practices. Develop end-to-end data solutions leveraging Azure services, including Azure Synapse Analytics, Azure Data Factory, Databricks, and Azure SQL. Define data models, integration patterns, and governance frameworks to ensure efficient data management, interoperability, and compliance. Drive cloud migration strategies for NHS More ❯

solutions align with NHS requirements and best practices. Develop end-to-end data solutions leveraging Azure services, including Azure Synapse Analytics, Azure Data Factory, Databricks, and Azure SQL. Define data models, integration patterns, and governance frameworks to ensure efficient data management, interoperability, and compliance. Drive cloud migration strategies for NHS More ❯

etc. Knowledge of Azure Data Factory/GCP Cloud Data Fusion, Microsoft Azure Machine Learning or GCP Cloud ML Engine, Azure Data Lake, Azure Databricks or GCP Cloud Dataproc. Familiarity with big data technologies and distributed computing frameworks, such as Hadoop, Spark, or Apache Flink. Experience scaling an “API-Ecosystem More ❯

solutions align with NHS requirements and best practices. Develop end-to-end data solutions leveraging Azure services, including Azure Synapse Analytics, Azure Data Factory, Databricks, and Azure SQL. Define data models, integration patterns, and governance frameworks to ensure efficient data management, interoperability, and compliance. Drive cloud migration strategies for NHS More ❯

etc. Knowledge of Azure Data Factory/GCP Cloud Data Fusion, Microsoft Azure Machine Learning or GCP Cloud ML Engine, Azure Data Lake, Azure Databricks or GCP Cloud Dataproc. Experience scaling an “API-Ecosystem”, designing, and implementing “API-First” integration patterns. Experience working with authentication and authorization protocols/patterns. More ❯

for are: Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache Airflow, Dagster, and Astronomer. GPU Computing: Familiarity with GPU computing, both on-premises and More ❯

align:justify"- -Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache Airflow, Dagster, and Astronomer. -GPU Computing: Familiarity with GPU computing, both on-premises and More ❯

cloud-centric environment. Familiarity with network access solutions (CASBs/Prisma/NAC) is advantageous. A passion for working in high-growth environments. About Databricks: Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune … rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake, and MLflow. Benefits: At Databricks, we strive to provide comprehensive benefits … perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit mybenefitsnow.com/databricks . Our Commitment to Diversity and Inclusion: At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take More ❯

pipeline patterns. Experience required: Insurance/financial services domain knowledge (preferred) Expertise in at least two of these key technologies: Azure, Azure Data Lake, Databricks, Matillion, Snowflake and Power BI (must have) Analytical system data architecture and ETL design experience Hands on experience in designing and implementing a data warehouse More ❯

data pipeline design and flow management. Practical experience with Kafka or RabbitMQ . Familiarity with microservices architecture and cloud-based data tools (e.g., Azure Databricks ). Understanding of data storage , performance optimisation, and security. Experience working in an agile environment and collaborating with cross-functional teams. Fluency in English , with More ❯

with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL/ELT pipelines . Proficiency More ❯

the role Expert SQL, Power BI, and data modelling. Familiarity working in an Azure environment (ADF ideal). Strong communication and stakeholder management skills. Databricks or Python desirable (not essential at all). My client are looking to book in first stage interviews for later this week and slots are More ❯

with private and public sector clients, including participating in RFI/RFP processes, preparing bids, and delivering presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions on Cloud platforms (AWS, Azure, Google Cloud) using provisioning tools More ❯

clients in unlocking actionable insights from their data. The Successful Data Engineer will have: Extensive experience in Azure technologies , including Azure Data Factory, Azure Databricks, Azure Synapse, and other relevant tools. Strong proficiency in data engineering principles , with expertise in building scalable, performant, and maintainable data pipelines. A deep understanding More ❯

various industry sectors is advantageous. Understanding of data management best practices, including data profiling, sourcing, cleansing routines, standardization, transformation, and matching. Good knowledge of Databricks, Snowflake, Azure, AWS, Oracle Cloud, R, and Python. Company Description Version 1 has over 28 years of experience in Technology Services, trusted by global brands. More ❯