1 to 25 of 335 Remote Databricks Jobs

learning and Data science applications Ability to use wide variety of open-source technologies Knowledge and experience using at least one Data Platform Technology such as Quantexa, Palantir and DataBricks Knowledge of test automation frameworks and ability to automate testing within the pipeline To discuss this or wider Technology roles with our recruitment team, all you need to do is More ❯

availability of data assets. Experience: 3-5 years of hands-on experience as a Data Engineer working in Azure cloud environments. Strong proficiency in Azure Data Factory, Synapse Analytics, Databricks, and Azure SQL. Solid understanding of data modeling, ETL/ELT design, and data warehousing principles. Proficiency in SQL and Python for data transformation and automation. Experience working with version More ❯

. Familiarity with Snowflake cost monitoring, governance, replication , and environment management. Strong understanding of data modelling (star/snowflake schemas, SCDs, lineage). Proven Azure experience (Data Factory, Synapse, Databricks) for orchestration and integration. Proficient in SQL for complex analytical transformations and optimisations. Comfortable working in agile teams and using Azure DevOps for CI/CD workflows. Nice to Have More ❯

development of data products. Desirable experience would be to have: Experience of working in an Agile Team; preferably Safe. Experience in specific tooling Qlik Replicate/Qlik Compose/DataBricks/Informatica/SAS An understanding of data modelling methodology (Kimball, Data Vault, Lakehouse) Understanding of Data Science, AI and Machine Learning ways of working About us Were one of More ❯

development of data products. Desirable experience would be to have: Experience of working in an Agile Team; preferably Safe. Experience in specific tooling Qlik Replicate/Qlik Compose/DataBricks/Informatica/SAS An understanding of data modelling methodology (Kimball, Data Vault, Lakehouse) Understanding of Data Science, AI and Machine Learning ways of working About us Were one of More ❯

AWS, GCP, or Azure), infrastructure-as-code practices, and ideally container orchestration with Kubernetes. Familiarity with SQL and NoSQL databases (Cassandra, Postgres), ideally combined with data collaboration platforms (Snowflake, Databricks) Strong DevOps mindset with experience in CI/CD pipelines, monitoring, and observability tools (Grafana or equivalent). Exposure to analytics, reporting, and BI tools such as Apache Superset, Lightdash More ❯

challenges. Culture builder, driving continuous improvement and operational excellence. Deep expertise in data compliance frameworks, cost management, and platform optimisation. Strong hands-on experience with modern cloud data warehouses (Databricks, Snowflake, AWS), SQL, Spark, Airflow, Terraform. Advanced Python skills with orchestration tooling; solid experience in CI/CD (Git, Jenkins). Proven track record in data modelling, batch/real More ❯

or similar platforms. Strong understanding of data warehousing concepts, data modelling, and ETL processes. Strong understanding of SAP Datasphere and basic knowledge of SAP Business data cloud and Azure Databricks Excellent analytical and problem-solving skills, with the ability to work with complex data sets. Strong communication and interpersonal skills, with the ability to collaborate effectively with technical and non More ❯

smooth releases and integration. Key Skills Data Modelling Python & SQL AWS/Redshift 3–5+ years of experience in data engineering Nice to Have Airflow, Tableau, Power BI, Snowflake, Databricks Data governance/data quality tooling Degree preferred Atlassian/Jira, CI/CD, Terraform Why Join? Career Growth: Clear progression to Tech Lead. Variety: Exposure to multiple squads and More ❯

kinds of data, and collaborating with both technical and non-technical teammates, this role is for you. What Youll Do Build and manage data pipelines in Azure (Data Factory, Databricks, Synapse, etc.). Pull in data from different sourcesAPIs, databases, cloud apps, even streaming data. Organize, clean, and transform data so its ready for reporting, dashboards, or advanced analytics. Keep More ❯

. Familiarity with Snowflake cost monitoring, governance, replication , and environment management. Strong understanding of data modelling (star/snowflake schemas, SCDs, lineage). Proven Azure experience (Data Factory, Synapse, Databricks) for orchestration and integration. Proficient in SQL for complex analytical transformations and optimisations. Comfortable working in agile teams and using Azure DevOps for CI/CD workflows. Prior experience in More ❯

. Familiarity with Snowflake cost monitoring, governance, replication , and environment management. Strong understanding of data modelling (star/snowflake schemas, SCDs, lineage). Proven Azure experience (Data Factory, Synapse, Databricks) for orchestration and integration. Proficient in SQL for complex analytical transformations and optimisations. Comfortable working in agile teams and using Azure DevOps for CI/CD workflows. Prior experience in More ❯

data quality, governance, and compliance processes Skills & experience required • Proven background leading data engineering teams or projects in a technology-driven business • Expert knowledge of modern cloud data platforms (Databricks, Snowflake, ideally AWS) • Advanced Python programming skills and fluency with the wider Python data toolkit • Strong capability with SQL, Spark, Airflow, Terraform, and workflow orchestration tools • Solid understanding of CICD More ❯

and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one builder who thrives on autonomy and ambiguity. Are a strong More ❯

and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one builder who thrives on autonomy and ambiguity. Are a strong More ❯

basis your varied role will include, but will not be limited to: Design, build, and optimize high-performance data pipelines and ETL workflows using tools like Azure Synapse, Azure Databricks or Microsoft Fabric. Implement scalable solutions to ingest, store, and transform vast datasets, ensuring data availability and quality across the organization. Write clean, efficient, and reusable Python code tailored to More ❯

with hands-on experience in relational and dimensional data modelling. Modern Data Engineering: Proven ability to design and deliver scalable solutions using tools like Microsoft Fabric (strongly preferred), Synapse, Databricks, or similar. Supporting Know-How: Solid grasp of data architecture, governance and security. DevOps & Cloud Fluency: Practical experience with CI/CD pipelines, APIs, and cloud tooling (eg Azure DevOps More ❯

12+ years of experience in a customer facing technical role and a working experience in: Distributed systems and massively parallel processing technologies and concepts such as Snowflake, Teradata, Spark, Databricks, Hadoop, Oracle, SQL Server, and performance optimisation Data strategies and methodologies such as Data Mesh, Data Vault, Data Fabric, Data Governance, Data Management, Enterprise Architecture Data organisation and modelling concepts More ❯

years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. · 3+ years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines · 3+ years of proficiency in working with Snowflake or similar cloud-based data warehousing solutions · 3+ years of experience in data development and More ❯

ownership/stewardship, data quality, data security, and data architecture. Experience in the energy trading sector or similarly data-rich environments. Experience with data platforms and tools (e.g., Azure, Databricks, MSSQL, Kafka). Hands-on experience developing conceptual, logical, and physical data models. Interest in the latest technologies and automation, with a curiosity to research and innovate Person Specification Taking More ❯

Skilled in team collaboration and exhibits good interpersonal skills. Able to prioritise, multi-task, and deliver at pace with an iterative mindset. Experience with modern data platforms such as Databricks or Snowflake is advantageous; LLM API experience is a bonus. Additional Information What’s in it for you?: Competitive salary that reflects your skills, experience and potential. Discretionary bonus scheme More ❯

technologies in data engineering, and continuously improve your skills and knowledge. Profile The Data Engineer will have mastery of data management and processing tools, including Power BI, Data Factory, Databricks, SQL Server, and Oracle. Proficient in SQL and experienced in database administration. Familiarity with cloud platforms such as Azure and AWS. Excellent problem-solving and analytical skills, with strong attention More ❯

and public sector clients (or internal clients within large organisations) through RFI/RFP responses, bid documentation, and client presentations. Hands-on experience with data science platforms such as Databricks , Dataiku , AzureML , or SageMaker , and machine learning frameworks such as TensorFlow , Keras , PyTorch , and scikit-learn . Expertise in cloud platforms ( AWS , Azure , Google Cloud ) and experience deploying solutions using More ❯

and public sector clients (or internal clients within large organisations) through RFI/RFP responses, bid documentation, and client presentations. Hands-on experience with data science platforms such as Databricks , Dataiku , AzureML , or SageMaker , and machine learning frameworks such as TensorFlow , Keras , PyTorch , and scikit-learn . Expertise in cloud platforms ( AWS , Azure , Google Cloud ) and experience deploying solutions using More ❯

design and long-term operation. Help refine and evolve engineering principles, development standards, and best practice. Skills & Experience: Hands-on experience with Azure data services such as Data Factory, Databricks, Data Lake, Azure SQL, Synapse, Data Catalog, and Purview. Strong Python and SQL skills for transformation and pipeline development. Solid understanding of Azure data storage/warehouse technologies including SQL More ❯