1 to 25 of 63 PySpark Jobs in London

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

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

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

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

Azure Storage. Excellent SQL and data modelling (star/snowflake, dimensional modelling). Knowledge of Power BI dataflows, DAX, and RLS. Experience with Python, PySpark, or T-SQL for transformations. Understanding of CI/CD and DevOps (Git, YAML pipelines). Strong grasp of data governance, security, and performance

Azure Storage. Excellent SQL and data modelling (star/snowflake, dimensional modelling). Knowledge of Power BI dataflows, DAX, and RLS. Experience with Python, PySpark, or T-SQL for transformations. Understanding of CI/CD and DevOps (Git, YAML pipelines). Strong grasp of data governance, security, and performance

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

office. About you : You have strong Python backend software engineer skills You have experience working with large data sets You have experience of using PySpark and ideally also Apache Spark You believe in automating wherever possible You're a collaborative problem solver with great communication skills Other technology

Experience as a Senior Data Engineer or similar Strong knowledge of Azure Cloud architecture and Azure Databricks, DevOps and CI/CD. Experience with PySpark, Python, SQL and other data engineering development tools. Experience with metadata driven pipelines and SQL serverless data warehouses. Knowledge of querying API systems. Experience

Experience as a Senior Data Engineer or similar Strong knowledge of Azure Cloud architecture and Azure Databricks, DevOps and CI/CD. Experience with PySpark, Python, SQL and other data engineering development tools. Experience with metadata driven pipelines and SQL serverless data warehouses. Knowledge of querying API systems. Experience

Experience as a Senior Data Engineer or similar Strong knowledge of Azure Cloud architecture and Azure Databricks, DevOps and CI/CD. Experience with PySpark, Python, SQL and other data engineering development tools. Experience with metadata driven pipelines and SQL serverless data warehouses. Knowledge of querying API systems. Experience

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

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

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

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

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

integrations using AWS PaaS such as Glue, EMR, Sagemaker, Redshift, Aurora and Snowflake Building data processing and analytics pipelines as code, using Python, SQL, PySpark, spark, CloudFormation, lambda, step functions, Apache Airflow Monitoring and reporting on the data platform performance, usage and security Designing and applying security and access

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

Continuously improve data systems and maintain awareness of best practice and emerging approaches Essential Skills Experience with large-scale analytics engines (e.g. Spark/PySpark) and scripting languages such as Python or Scala. Hands-on use of cloud data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage

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

agentic capabilities, able to build production-grade applications not just prototypes. Strong proficiency in at least one relevant programming language such as Python or PySpark, Java, Typescript or SQL. Solid understanding of data engineering, data modelling, security and governance in enterprise settings. Experience with software engineering best practices including

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

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

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