226 to 250 of 744 Remote Databricks Jobs

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

data assets. Learn from and collaborate with senior engineers. Capabilities 2+ years relevant work experience. Foundational experience with Python and SQL. Eagerness to work with tools like dbt, Spark, DataBricks, and Kedro. Understanding of version control, testing, and documentation. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data Engineer Responsibilities Build and More ❯

with DevOps culture and agile software delivery methods Nice to have: AWS and/or FME Certifications Familiarity with ETL tools such as AWS Glue, Azure Data Factory, or Databricks Why Join? This role offers the best of both worlds: the autonomy of a principal technical lead and the purpose of delivering public-good technology . You’ll be joining More ❯

or internal clients within large organisations, through e.g. the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including More ❯

technologies like Snowflake, BigQuery, Redshift Experience in open source technologies like Spark, Kafka, Beam Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in an agile environment Here’s a taste of the perks we roll out for our extraordinary team members: 25 Days of Holiday, plus 8 Bank Holidays: We More ❯

to learn and stay updated with the latest technologies in the field of data engineering Strong organizational and time management skills Advantageous skills/experience: Hands-on experience with Databricks, including development, implementation, and optimization in large-scale environments. Experience with AWS. Experience with SQL server SSIS packages. Experience with reporting tools AWS QuickSight, PowerBI. SMART Values S peak Openly More ❯

engineering, software testing, or test automation . Familiarity with testing data pipelines, ETL/ELT workflows, and big data solutions . Experience with cloud-based data platforms , preferably Azure Databricks, Azure Data Factory, or Synapse Analytics . Basic experience with test automation frameworks (e.g., PyTest, Great Expectations, DBT tests, or similar). Proficiency in SQL and scripting languages (e.g., Python More ❯

working with third-party providers. Knowledge of Lloyds Insurance and Reinsurance, Finance GAAP, Actuarial Reserves, Regulatory Reports, Databases (Data Warehouse, T-SQL, SSIS, SQL Server 2019), ETL processes with Databricks, Programming languages (e.g., Python), AWS, Agile methodologies, Jira, and MS Office products. Educational background with a BSc degree or higher in a relevant field. What is a Must Have? Bachelor More ❯

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 ❯

strong technical understanding and interest in engineering reliable and maintainable data products. You will be experienced in a range of technologies including: Python & SQL languages Distributed data processing (e.g. Databricks, Apache Spark, AWS Glue) Data integration techniques (e.g. API, ELT/ETL) Decentralised version control systems (e.g. git, mercurial) Testing You will also possess programming and build skills with the More ❯

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 ❯

data streaming and event-driven architectures, with a focus on Kafka and Confluent platforms. In-depth knowledge in architecting and implementing data lakes and lakehouse platforms, including experience with Databricks and Unity Catalog. Proficiency in conceptualising and applying Data Mesh and Data Fabric architectural patterns. Experience in developing data product strategies, with a strong inclination towards a product-led approach More ❯

data streaming and event-driven architectures, with a focus on Kafka and Confluent platforms. In-depth knowledge in architecting and implementing data lakes and lakehouse platforms, including experience with Databricks and Unity Catalog. Proficiency in conceptualising and applying Data Mesh and Data Fabric architectural patterns. Experience in developing data product strategies, with a strong inclination towards a product-led approach More ❯

best practice. Desirable Exposure to data modelling, data quality, data warehousing, data governance and security best practices. Exposure to Python for data engineering and data platforms like MS Fabric, Databricks, etc Public cloud provider experience(AWS, Azure, GCP) What you get from us: If you're looking to build an exceptional career with an award-winning company you've come More ❯

RAG frameworks: Use techniques such as chunking, hybrid search, query translation, similarity search, vector DBs, evaluation metrics, and ANN algorithms. Monitoring performance: Using observability services such as Datadog and Databricks for LLM Observability and analytics. Keep track of latest research: Given that this is a fast evolving field, it’s important to keep track of the latest advancements in fine More ❯

role. Experience with Agile/Scrum Framework. Excellent problem-solving and analytical skills. Excellent communication skills, both at a deep technical level and stakeholder level. Data Expert experience with Databricks (PySpark). Experience building and maintaining complex ETL Projects, end-to-end (ingestion, processing, storage). Expert knowledge and experience with data modelling, data access, and data storage techniques. Experience More ❯

value through tailored software presentations and overcoming technical objections Expertise in cloud computing platforms such as AWS, GCP, or Azure, and experience with Cloud Data Platforms like Snowflake and Databricks In-depth understanding of relational databases (PostgreSQL, MySQL, Oracle, SQL Server) and NoSQL databases (MongoDB, Cassandra, DynamoDB) Hands-on experience with technical problem-solving and integration technologies (APIs, Linux, SQL More ❯

years. More information on SC Clearance checks can be found here Responsibilities Designing cloud-based data platforms and data solutions using a wide range of Azure Services including Azure Databricks, Azure SQL Database, Azure Data Lake Storage, Azure Synapse, Azure Cosmos DB, Azure Data Factory and Azure Blob storage Building conceptual, logical and physical data models optimised for analytical use More ❯

experience in IaC and able to guide how one could deploy infrastructure into different environments. Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop. Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes) Ability to create data pipelines on a cloud environment and integrate More ❯