1 to 25 of 73 PySpark Jobs in the UK excluding London

on data strategy, risk mitigation, and platform evolution. Mentor and develop data engineering talent, fostering a high-performance culture. Requirements: Extensive hands-on experience with AWS data tools: Glue, PySpark, Athena, Iceberg, Lake Formation. Strong proficiency in Python and SQL. Proven leadership in data engineering strategy and execution. Deep understanding of market data and its business applications. Experience with More ❯

data modeling, data warehousing concepts, and distributed systems. Excellent problem-solving skills and ability to progress with design, build and validate output data independently. Deep proficiency in Python (including PySpark), SQL, and cloud-based data engineering tools. Expertise in multiple cloud platforms (AWS, GCP, or Azure) and managing cloud-based data infrastructure. Strong background in database technologies (SQL Server More ❯

data modeling, data warehousing concepts, and distributed systems. Excellent problem-solving skills and ability to progress with design, build and validate output data independently. Deep proficiency in Python (including PySpark), SQL, and cloud-based data engineering tools. Expertise in multiple cloud platforms (AWS, GCP, or Azure) and managing cloud-based data infrastructure. Strong background in database technologies (SQL Server More ❯

data modeling, data warehousing concepts, and distributed systems. Excellent problem-solving skills and ability to progress with design, build and validate output data independently. Deep proficiency in Python (including PySpark), SQL, and cloud-based data engineering tools. Expertise in multiple cloud platforms (AWS, GCP, or Azure) and managing cloud-based data infrastructure. Strong background in database technologies (SQL Server More ❯

an impact, get in touch ASAP as interviews are already taking place. Don't miss out! Key Skills: AWS, Data, Architecture, Data Engineering, Data Warehousing, Data Lakes, Databricks, Glue, Pyspark, Athena, Python, SQL, Machine Learning, London More ❯

including Azure DevOps or GitHub Considerable experience designing and building operationally efficient pipelines, utilising core Cloud components, such as Azure Data Factory, Big Query, AirFlow, Google Cloud Composer and Pyspark etc Proven experience in modelling data through a medallion-based architecture, with curated dimensional models in the gold layer built for analytical use Strong understanding and or use of More ❯

regular company events What you'll need: Solid experience in data engineering, management and analysis Strong experience with Azure Data Warehouse solutions and AWS Databricks platforms Exceptional Python/PySpark + additional languages for data processing Strong SQL with experience across both relational databases (SQL Server, MySQL) and NoSQL solutions (MongoDB, Cassandra) Hands-on knowledge of AWS S3 and More ❯

data tooling such as Synapse Analytics, Microsoft Fabric, Azure Data Lake Storage/One Lake, and Azure Data Factory. Understanding of data extraction from vendor REST APIs. Spark/Pyspark or Python skills a bonus or a willingness to develop these skills. Experience with monitoring and failure recovery in data pipelines. Excellent problem-solving skills and attention to detail. More ❯

knowledge sharing sessions and self-development. About You Experience with finance/financial systems and concepts Azure Databricks Azure Data Factory Excellent SQL skills Good Python/Spark/pyspark skills Experience of Kimball Methodology and star schemas (dimensional model). Experience of working with enterprise data warehouse solutions. Experience of working with structured and unstructured data Experience of More ❯

Drive automation and CI/CD practices across the data platform Explore new technologies to improve data ingestion and self-service Essential Skills Azure Databricks : Expert in Spark (SQL, PySpark), Databricks Workflows Data Pipeline Design : Proven experience in scalable ETL/ELT development Azure Services : Data Lake, Blob Storage, Synapse Data Governance : Unity Catalog, access control, metadata management Performance More ❯

It is entering a phase of hardening and re-engineering to enhance the speed, ease, and quality of ingestion across the portfolio. Key Requirements: Strong proficiency in Python and PySpark Successful track history in a Data Engineering role including Database Management (ideally SQL), Data Orchestration (ideally Apache Airflow or Dagster), Containerisation (ideally Kubernetes and Docker) .Data Pipelines (big data More ❯

Microsoft Azure data services (Azure Data Factory, Azure Data Fabric, Azure Synapse Analytics, Azure SQL Database). Experience building ELT/ETL pipelines and managing data workflows. Proficiency in PySpark, Python, SQL, or Scala. Strong data modelling and relational database knowledge. Solid understanding of GDPR and UK data protection. Preferred Power BI experience. Familiarity with legal industry platforms. Awareness More ❯

Microsoft Azure data services (Azure Data Factory, Azure Data Fabric, Azure Synapse Analytics, Azure SQL Database). Experience building ELT/ETL pipelines and managing data workflows. Proficiency in PySpark, Python, SQL, or Scala. Strong data modelling and relational database knowledge. Solid understanding of GDPR and UK data protection. Preferred Power BI experience. Familiarity with legal industry platforms. Awareness More ❯

financial datasets Python experience, particularly for data processing and ETL workflows Hands-on experience with cloud platforms- Azure Experience designing and maintaining data pipelines using tools like Databricks and PySpark Knowledge of data warehousing solutions - Snowflake experience would be brilliant Understanding of CI/CD processes for deploying data solutions Some exposure to big data technologies and distributed processing More ❯

within Microsoft Azure data tools (Azure Data Factory, Azure Synapse, or Azure SQL). ✅ Dimensional modelling expertise for analytics use cases. ✅ Strong ETL/ELT development skills. ✅ Python/Pyspark experience ✅ Experience with CI/CD methodologies for data platforms. ✅ Deep knowledge of SQL ✅ Extensive London Markets experience Why Join? 🚀 New Projects – Work on a new data platform, shaping More ❯

within Microsoft Azure data tools (Azure Data Factory, Azure Synapse, or Azure SQL). ✅ Dimensional modelling expertise for analytics use cases. ✅ Strong ETL/ELT development skills. ✅ Python/Pyspark experience ✅ Experience with CI/CD methodologies for data platforms. ✅ Deep knowledge of SQL ✅ Extensive London Markets experience Why Join? 🚀 New Projects – Work on a new data platform, shaping More ❯

within Microsoft Azure data tools (Azure Data Factory, Azure Synapse, or Azure SQL). ✅ Dimensional modelling expertise for analytics use cases. ✅ Strong ETL/ELT development skills. ✅ Python/Pyspark experience ✅ Experience with CI/CD methodologies for data platforms. ✅ Deep knowledge of SQL ✅ Extensive London Markets experience Why Join? 🚀 New Projects – Work on a new data platform, shaping More ❯

workflows and processes What were looking for: 5+ years of experience in data engineering or related roles Proficiency in Python, Java, Golang, Spark, Azure, Synapse Analytics, SQL, Datalake Technology, PySpark, Python, Azure Functions, Azure Data Factory Nice to have: Scala. Familiarity with Kepler geospatial visualisation tool, or other similar tools, and experience working with geospatial data would also be More ❯

the ability to write ad-hoc and complex queries to perform data analysis. Experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. You will be able to develop solutions in a hybrid data environment (on-Prem and Cloud). Hands on experience with developing data pipelines for structured, semi-structured More ❯

Azure. Especially Synapse, ADF and Power BI (Datasets and Reports). Ideally SSIS, SSRS, SSAS with some understanding of Power App design and delivery Expert in SQL and Python (PySpark) languages, any other object orientated language skills would be a benefit Expert in data modelling and data architecture concepts Experience of setup and management of code management & deployment tools More ❯

Engineer/Data Engineering role Large and complex datasets Azure, Azure Databricks Microsoft SQL Server Lakehouse, Delta Lake Data Warehousing ETL CDC Stream Processing Database Design ML Python/PySpark Azure Blob Storage Parquet Azure Data Factory Desirable: Any exposure working in a software house, consultancy, retail or retail automotive sector would be beneficial but not essential. 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 ❯

Troubleshoot issues and continuously improve data infrastructure Explore AI-driven enhancements to boost data accuracy and productivity Requirements: Strong experience with: Azure Databricks, Data Factory, Blob Storage Python/PySpark SQL Server, Parquet, Delta Lake Deep understanding of: ETL/ELT, CDC, stream processing Lakehouse architecture and data warehousing Scalable pipeline design and database optimisation A proactive mindset, strong More ❯

and dimensional data models, and contribute to fostering a culture of innovation and evidence led decision-making. Experience Required: ·Essential experience with Azure Databricks - including Unity Catalog, Python (ideally PySpark), and SQL. ·Practical knowledge of modern ELT workflows, with a focus on the Extract and Load stages. ·Experience working across both technical and non-technical teams, with the ability More ❯

and dimensional data models, and contribute to fostering a culture of innovation and evidence led decision-making. Experience Required: Essential experience with Azure Databricks – including Unity Catalog, Python (ideally PySpark), and SQL. Practical knowledge of modern ELT workflows, with a focus on the Extract and Load stages. Experience working across both technical and non-technical teams, with the ability More ❯