26 to 50 of 77 Remote PySpark Jobs

build skills and knowledge relevant to the role. Essential Skills Experience of using a unified engine for large-scale data analytics (e.g. Spark/PySpark) Experience in writing, testing and implementing scripts (e.g. Python, Scala) Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena) Communicating technical

build skills and knowledge relevant to the role. Essential Skills Experience of using a unified engine for large-scale data analytics (e.g. Spark/PySpark) Experience in writing, testing and implementing scripts (e.g. Python, Scala) Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena) Communicating technical

data pipelines using Azure services such as Synapse, Data Factory or Databricks Commercial experience with Microsoft Fabric Strong understanding of SQL and Python/PySpark Experience with Power BI and data modelling Some of the package/role details include: Salary up to £85,000 Flexible hybrid working model

data pipelines using Azure services such as Synapse, Data Factory or Databricks Commercial experience with Microsoft Fabric Strong understanding of SQL and Python/PySpark Experience with Power BI and data modelling Some of the package/role details include: Salary up to £85,000 Flexible hybrid working model

product teams who'll challenge them in the best ways The ideal candidate will: Know their way around AWS data tools (Glue/PySpark, Athena) and Microsoft Fabric Be able to write clean Python and SQL in their sleep Have battle scars from integrating CRMs (HubSpot, Salesforce) via APIs

Active Security Clearance (SC) Strong Python skills with modular, test-driven design Experience with Behave for unit and BDD testing (mocking, patching) Proficiency in PySpark and distributed Data processing Solid understanding of Delta Lake (design and maintenance) Hands-on with Docker for development and deployment Familiarity with Azure services

Active Security Clearance (SC) Strong Python skills with modular, test-driven design Experience with Behave for unit and BDD testing (mocking, patching) Proficiency in PySpark and distributed Data processing Solid understanding of Delta Lake (design and maintenance) Hands-on with Docker for development and deployment Familiarity with Azure services

Strong knowledge of AWS data services (Glue, S3, Lambda, Redshift, etc.) Solid understanding of ETL processes and data pipeline management Proficiency in Python and PySpark Experience working with SQL-based platforms Previous involvement in migrating on-premise solutions to cloud is highly desirable Excellent collaboration skills and ability

data stack, including Databricks and Data Factory, to help us build and optimise cutting-edge solutions. You'll bring strong programming skills in Python, PySpark, and SQL, along with proven experience in designing data models, developing pipelines, and implementing modern data architecture. Your ability to translate complex technical concepts

Strong knowledge of ETL processes is essential, including experience with tools such as Talend, Informatica, Matillion, Pentaho, MuleSoft, Boomi, or scripting languages like Python, PySpark, and SQL. A solid understanding of data warehousing and modelling techniques, including Star and Snowflake schemas, is required. Ideally you will also have

presenting to clients or colleagues Industry experience in the retail banking or wider financial services sector Additional technical experience in any of the following – PySpark, Microsoft Azure, VBA, HTML/CSS, JavaScript, JQuery, SQL, PHP, Power Automate, Power BI What we offer A highly competitive salary A genuinely compelling

Databricks-based data warehousing solution Designing and developing data models, ETL pipelines, and data integration processes Large scale data processing using PySpark Monitoring, tuning, and optimising data platforms for reliability and performance Upskilling the wider team in Databricks best practices, including modern architecture patterns Location: Atherstone (Hybrid – 3 days

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

Elevate team capabilities by setting best practices in analytics, code quality, and data storytelling. DIMENSIONS AND ASPECTS Technical expertise : Proven hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau), with advanced Excel skills for rapid analysis. Analytical leadership : Demonstrated ability to proactively identify

data governance, security, and compliance. Key Skills & Experience* Proven experience as an Azure Data Engineer.* Strong hands-on expertise with Databricks - 5+ years experience (PySpark, notebooks, clusters, Delta Lake).* Solid knowledge of Azure services (Data Lake, Synapse, Data Factory, Event Hub).* Experience working with DevOps teams

enabling advanced analytics and data-driven decision making across the business. Key Responsibilities Design, develop, and maintain ETL/ELT pipelines using Azure Databricks, PySpark, and Delta Lake. Build and optimise data lakehouse architectures on Azure Data Lake Storage ( ADLS ) . Develop high-performance data solutions using Azure Synapse … Actions, or Azure DevOps Required Skills & Experience 3+ years' experience as a Data Engineer working in Azure environments. Strong hands-on experience with Databricks (PySpark, Delta Lake, cluster optimisation, job scheduling). Solid knowledge of Azure cloud services including: Azure Data Lake Storage Azure Data Factory Azure Synapse/

enabling advanced analytics and data-driven decision making across the business. Key Responsibilities Design, develop, and maintain ETL/ELT pipelines using Azure Databricks, PySpark, and Delta Lake. Build and optimise data lakehouse architectures on Azure Data Lake Storage ( ADLS ) . Develop high-performance data solutions using Azure Synapse … Actions, or Azure DevOps Required Skills & Experience 3+ years' experience as a Data Engineer working in Azure environments. Strong hands-on experience with Databricks (PySpark, Delta Lake, cluster optimisation, job scheduling). Solid knowledge of Azure cloud services including: Azure Data Lake Storage Azure Data Factory Azure Synapse/

TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate models into production environments. Monitor model performance and retrain as needed to ensure accuracy and efficiency. Collaborate with cross-functional teams