1 to 25 of 44 PySpark Jobs in the City of London

in Computer Science, Software Engineering, or equivalent technical discipline. 8+ years of hands-on experience building large-scale distributed data pipelines and architectures. Expert-level knowledge in Apache Spark, PySpark, and Databricks—including experience with Delta Lake, Unity Catalog, MLflow, and Databricks Workflows. Deep proficiency in Python and SQL, with proven experience building modular, testable, reusable pipeline components. Strong More ❯

to logically analyse complex requirements, processes, and systems to deliver solutions. Solid understanding of data modelling, ETL/ELT processes, and data warehousing. Proficiency in SQL and Python (especially PySpark), as well as other relevant programming languages. Passion for using data to drive key business decisions. Skills we’d love to see/Amazing Extras: Experience with Microsoft Fabric. More ❯

salary, equity, and benefits. Join a supportive, high-calibre engineering team committed to quality and innovation. 📍 Location: Paddington, London 💻 Tech Stack: Python, SQL, dbt, Databricks, Azure, GCP, Airflow, Terraform, PySpark More ❯

are an experienced Data Engineer within financial services environments You have expertise with GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with More ❯

Azure cloud data lakes and services (Data Factory, Synapse, Databricks). Skilled in ETL/ELT pipeline development and big data tools (Spark, Hadoop, Kafka). Strong Python/PySpark programming and advanced SQL with query optimisation. Experience with relational, NoSQL, and graph databases. Familiar with CI/CD, version control, and infrastructure as code (Terraform). Strong analytical More ❯

Requirements: 10+ years in cloud architecture/engineering with a strong focus on building scalable data pipelines Expertise in Azure Databricks (7+years) including building and managing ETL pipelines using PySpark or Scala (essential) Solid understanding of Apache Spark, Delta Lake, and distributed data processing concepts Hands-on experience with Azure Data Lake Storage Gen2, Azure Data Factory, and Azure More ❯

leadership and upskilling responsibilities. Key Responsibilities Build and maintain Databricks Delta Live Tables (DLT) pipelines across Bronze → Silver → Gold layers, ensuring quality, scalability, and reliability. Develop and optimise Spark (PySpark) jobs for large-scale distributed processing. Design and implement streaming data pipelines with Kafka/MSK, applying best practices for late event handling and throughput. Use Terraform and CI More ❯

leadership and upskilling responsibilities. Key Responsibilities Build and maintain Databricks Delta Live Tables (DLT) pipelines across Bronze → Silver → Gold layers, ensuring quality, scalability, and reliability. Develop and optimise Spark (PySpark) jobs for large-scale distributed processing. Design and implement streaming data pipelines with Kafka/MSK, applying best practices for late event handling and throughput. Use Terraform and CI More ❯

and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik). Strong SQL and data modelling skills. Experience working with large, complex financial More ❯

and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik). Strong SQL and data modelling skills. Experience working with large, complex financial More ❯

data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD, code reviews, and More ❯

data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD, code reviews, and More ❯

having delivered in Microsoft Azure Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure Data Engineering certifications Databricks certifications What's in it for you: 📍Location: London (Hybrid) 💻Remote working: Occasional More ❯

having delivered in Microsoft Azure Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure Data Engineering certifications Databricks certifications What's in it for you: 📍Location: London (Hybrid) 💻Remote working: Occasional More ❯

data-driven culture all within a collaborative environment that values innovation and ownership. Tech you’ll be working with: Azure Data Lake Azure Synapse Databricks Data Factory Python, SQL, PySpark Terraform, GitHub Actions, CI/CD pipelines You’ll thrive here if you: Have strong experience building and leading Azure-based data platforms Enjoy mentoring and guiding other engineers 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 ❯

data-driven culture all within a collaborative environment that values innovation and ownership. Tech you’ll be working with: Azure Data Lake Azure Synapse Databricks Data Factory Python, SQL, PySpark Terraform, GitHub Actions, CI/CD pipelines You’ll thrive here if you: Have strong experience building and leading Azure-based data platforms Enjoy mentoring and guiding other engineers More ❯

improve AI models over time. REQUIREMENTS 2 years of proven experience in data engineering for ML/AI, with strong proficiency in Python, SQL, and distributed data processing (e.g., PySpark). Hands-on experience with cloud data platforms (GCP, AWS, or Azure), orchestration frameworks (e.g., Airflow), and ELT/ETL tools. Familiarity with 2D and 3D data formats (e.g. More ❯

improve AI models over time. REQUIREMENTS 2 years of proven experience in data engineering for ML/AI, with strong proficiency in Python, SQL, and distributed data processing (e.g., PySpark). Hands-on experience with cloud data platforms (GCP, AWS, or Azure), orchestration frameworks (e.g., Airflow), and ELT/ETL tools. Familiarity with 2D and 3D data formats (e.g. More ❯

Studio and data transformation logic Azure Fabric, Azure Data Factory, Synapse, Data Lakes and Lakehouse/Warehouse technologies ETL/ELT orchestration for structured and unstructured data Proficiency in: PySpark, T-SQL, Notebooks and advanced data manipulation Performance monitoring and orchestration of Fabric solutions Power BI semantic models and Fabric data modelling DevOps deployment using ARM/Bicep templates More ❯

Studio and data transformation logic Azure Fabric, Azure Data Factory, Synapse, Data Lakes and Lakehouse/Warehouse technologies ETL/ELT orchestration for structured and unstructured data Proficiency in: PySpark, T-SQL, Notebooks and advanced data manipulation Performance monitoring and orchestration of Fabric solutions Power BI semantic models and Fabric data modelling DevOps deployment using ARM/Bicep templates More ❯

and validate data models and outputs Set up monitoring and ensure data health for outputs What we are looking for Proficiency in Python, with experience in Apache Spark and PySpark Previous experience with data analytics softwares Ability to scope new integrations and translate user requirements into technical specifications What’s in it for you? Base salary of More ❯

and validate data models and outputs Set up monitoring and ensure data health for outputs What we are looking for Proficiency in Python, with experience in Apache Spark and PySpark Previous experience with data analytics softwares Ability to scope new integrations and translate user requirements into technical specifications What’s in it for you? Base salary of More ❯

London offices 1-2 days a week – based business need. To Be Considered: Demonstrable expertise and experience working on large-scale Data Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering More ❯

London offices 1-2 days a week – based business need. To Be Considered: Demonstrable expertise and experience working on large-scale Data Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering More ❯