1 to 25 of 87 PySpark Jobs in England

with multiple data analytics tools (e.g. Power BI) Deep understanding of data wareho using concepts, ETL/ELT pipelines and dimensional modelling Proficiency in advanced programming languages (Python/PySpark, SQL) Experience in data pipeline orchestration (e.g. Airflow, Data Factory) Familiarity with DevOps and CI/CD practices (Git, Azure DevOps etc) Ability to communicate technical concepts to both More ❯

reviews and continuous improvement initiatives Essential Skills for the AWS Data Engineer: Extensive hands-on experience with AWS data services Strong programming skills in Python (including libraries such as PySpark or Pandas) Solid understanding of data modelling, warehousing and architecture design within cloud environments Experience building and managing ETL/ELT workflows and data pipelines at scale Proficiency with More ❯

Storage . Implement governance and security measures across the platform. Leverage Terraform or similar IaC tools for controlled and reproducible deployments. Databricks Development Develop and optimise data jobs using PySpark or Scala within Databricks. Implement the medallion architecture (bronze, silver, gold layers) and use Delta Lake for reliable data transactions. Manage cluster configurations and CI/CD pipelines for More ❯

from APIs, databases, and financial data sources into Azure Databricks. Optimize pipelines for performance, reliability, and cost, incorporating data quality checks. Develop complex transformations and processing logic using Spark (PySpark/Scala) for cleaning, enrichment, and aggregation, ensuring accuracy and consistency across the data lifecycle. Work extensively with Unity Catalog, Delta Lake, Spark SQL, and related services. Apply best More ❯

from APIs, databases, and financial data sources into Azure Databricks. Optimize pipelines for performance, reliability, and cost, incorporating data quality checks. Develop complex transformations and processing logic using Spark (PySpark/Scala) for cleaning, enrichment, and aggregation, ensuring accuracy and consistency across the data lifecycle. Work extensively with Unity Catalog, Delta Lake, Spark SQL, and related services. Apply best More ❯

with Distributed computing frameworks knowledge: Hive/Hadoop, Apache Spark, Kafka, Airflow Working with programming languages Python , Java, SQL. Working on building ETL (Extraction Transformation and Loading) solution using PySpark Experience in SQL/NoSQL database design Deep understanding in software architecture, object oriented design principles, and data structures Extensive experience in developing microservices using Java, Python Good experience More ❯

and prompt engineering. Mandatory Skills: Cloud Platforms:Deep experience with AWS (S3, Lambda, Glue, Redshift) and/or Azure (Data Lake, Synapse). Programming & Scripting:Proficiency in Python, SQL, PySpark etc. ETL/ELT & Streaming:Expertise in technologies like Apache Airflow, Glue, Kafka, Informatica, EventBridge etc. Industrial Data Integration:Familiarity with OT data schema originating from OSIsoft PI, SCADA More ❯

to adapt quickly to changing environments and priorities, maintaining effectiveness in dynamic situations Proficiency using SQL Server in a highly transactional environment. Experience in either C# or Python/PySpark for data engineering or development tasks. Strong understanding of DevOps principles and experience with relevant tools e.g., Azure DevOps, Git, Terraform for CI/CD, automation, and infrastructure management. More ❯

Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks . Good proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage, and More ❯

build, and maintain scalable ETL pipelines to ingest, transform, and load data from diverse sources (APIs, databases, files) into Azure Databricks. Implement data cleaning, validation, and enrichment using Spark (PySpark/Scala) and related tools to ensure quality and consistency. Utilize Unity Catalog, Delta Lake, Spark SQL, and best practices for Databricks development, optimization, and deployment. Program in SQL More ❯

build, and maintain scalable ETL pipelines to ingest, transform, and load data from diverse sources (APIs, databases, files) into Azure Databricks. Implement data cleaning, validation, and enrichment using Spark (PySpark/Scala) and related tools to ensure quality and consistency. Utilize Unity Catalog, Delta Lake, Spark SQL, and best practices for Databricks development, optimization, and deployment. Program in SQL More ❯

experience as an Azure Data Engineer in enterprise environments. Strong hands-on expertise with Azure Data Factory , Databricks , Synapse , and Azure Data Lake . Proficiency in SQL , Python , and PySpark . Experience with data modelling , ETL optimisation , and cloud migration projects . Familiarity with Agile delivery and CI/CD pipelines. Excellent communication skills for working with technical and More ❯

experience as an Azure Data Engineer in enterprise environments. Strong hands-on expertise with Azure Data Factory , Databricks , Synapse , and Azure Data Lake . Proficiency in SQL , Python , and PySpark . Experience with data modelling , ETL optimisation , and cloud migration projects . Familiarity with Agile delivery and CI/CD pipelines. Excellent communication skills for working with technical and More ❯

as a Data Engineer or similar role. Strong experience with Azure data services (ADF, Databricks, ADLS, Synapse, Event Hub, etc.). Proficiency in SQL and experience with Python/PySpark . Hands-on experience building ETL/ELT pipelines in cloud environments. Solid understanding of data modelling, warehousing concepts, and distributed data systems. Experience with version control (Git) and More ❯

ETL/ELT development and orchestration tools (DBT, Airflow, or similar). Hands-on experience with cloud platforms (AWS, Azure, or GCP). Strong knowledge of SQL, Python, and PySpark for data processing. Familiarity with CI/CD pipelines and DevOps practices for data solutions. This role is perfect for someone who thrives on solving complex data challenges and More ❯

modelling techniques + data integration patterns. Experience of working with complex data pipelines, large data sets, data pipeline optimization + data architecture design. Implementing complex data transformations using Spark, PySpark or Scala + working with SQL/MySQL databases. Experience with data quality, data governance processes, Git version control + Agile development environments. Azure Data Engineer certification preferred -eg More ❯

and influence decisions. Strong understanding of data models and analytics; exposure to predictive modelling and machine learning is a plus. Proficient in SQL and Python, with bonus points for PySpark, SparkSQL, and Git. Skilled in data visualisation with tools such as Tableau or Power BI. Confident writing efficient code and troubleshooting sophisticated queries. Clear and adaptable communicator, able to More ❯

and monitoring. Data modelling expertise to develop low-level designs and implement models against business requirements, using design patterns such as Inmon, Kimball and Data Vault. Excellent Databricks, Python, PySpark and Spark SQL knowledge, including writing, testing and quality assuring code and knowledge of Unity Catalog best practice to govern data assets as well as Azure and/or More ❯

Essential Skills Include: Proven leadership and mentoring experience in senior data engineering roles Expertise in Azure Data Factory, Azure Databricks, and lakehouse architecture Strong programming skills (Python, T-SQL, PySpark) and test-driven development Deep understanding of data security, compliance, and tools like Microsoft Purview Excellent communication and stakeholder management skills Experience with containerisation and orchestration (e.g., Kubernetes, Azure More ❯

warehousing techniques, including the Kimball Methodology or other similar dimensional modelling standards, is essential to the role. Technical experience building and deploying models and reports utilizing the following tools: PySpark Microsoft Fabric or Databricks Power BI Git CI/CD pipelines (Azure DevOps experience preferred) An understanding of the structure and purpose of the Financial Advice and Wealth Management More ❯

Experience in a Data Engineer/Data Engineering role Large and complex datasets Azure, Azure Databricks Microsoft SQL Server Lakehouse, Delta Lake Data Warehousing ETL Database Design Python/PySpark Azure Blob Storage Azure Data Factory Desirable: Exposure ML/Machine Learning/AI/Artificial Intelligence More ❯

data models and transformation pipelines using Databricks, Azure, and Power BI to turn complex datasets into reliable, insight-ready assets. You'll apply strong skills in SQL, Python, and PySpark to build efficient ELT workflows and ensure data quality, performance, and governance. Collaboration will be key as you partner with analysts and business teams to align data models with More ❯

have: Hands-on experience creating 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 (normally once/twice per More ❯

have: Hands-on experience creating 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 (normally once/twice per More ❯

analytics Practical experience in coding language - e.g., Python, R, Scala, etc. (Python preferred) Strong proficiency in database technologies - e.g., SQL, ETL, No SQL, DW, and Big Data technologies - e.g., PySpark, Hive, etc. Experienced working with structured and also unstructured data - e.g., Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine tune More ❯