12 of 12 PySpark Jobs in Central 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 ❯

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 ❯

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 ❯

Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. Skillset Required: Experience in Python, PySpark and SQL Experience with AWS is a plus Strong proficiency in Core Java, including Collections, Concurrency, and Memory Management. Proficient in version control systems such as Git, GitLab, or More ❯

Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. Skillset Required: Experience in Python, PySpark and SQL Experience with AWS is a plus Strong proficiency in Core Java, including Collections, Concurrency, and Memory Management. Proficient in version control systems such as Git, GitLab, or 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 ❯

and experienced AWS Lead Data Engineer, who will build, and lead the development of scalable data pipelines and platforms on AWS. The ideal candidate will have deep expertise in PySpark, Glue, Athena, AWS LakeFormation, data modelling, DBT, Airflow, Docker and will be responsible for driving best practices in data engineering, governance, and DevOps. Key Responsibilities: • Lead the design and … implementation of scalable, secure, and high-performance data pipelines using PySpark and AWS Glue. • Architect and manage data lakes using AWS Lake Formation, ensuring proper access control and data governance. • Develop and optimize data models (dimensional and normalized) to support analytics and reporting. • Collaborate with analysts and business stakeholders to understand data requirements and deliver robust solutions. • Implement and … Engineering, or related field. • 10+ years of experience in data engineering. • Strong hands-on experience with AWS services: S3, Glue, Lake Formation, Athena, Redshift, Lambda, IAM, CloudWatch. • Proficiency in PySpark, Python, DBT, Airflow, Docker and SQL. • Deep understanding of data modeling techniques and best practices. • Experience with CI/CD tools and version control systems like Git. • Familiarity with More ❯

and experienced AWS Lead Data Engineer, who will build, and lead the development of scalable data pipelines and platforms on AWS. The ideal candidate will have deep expertise in PySpark, Glue, Athena, AWS LakeFormation, data modelling, DBT, Airflow, Docker and will be responsible for driving best practices in data engineering, governance, and DevOps. Key Responsibilities: • Lead the design and … implementation of scalable, secure, and high-performance data pipelines using PySpark and AWS Glue. • Architect and manage data lakes using AWS Lake Formation, ensuring proper access control and data governance. • Develop and optimize data models (dimensional and normalized) to support analytics and reporting. • Collaborate with analysts and business stakeholders to understand data requirements and deliver robust solutions. • Implement and … Engineering, or related field. • 10+ years of experience in data engineering. • Strong hands-on experience with AWS services: S3, Glue, Lake Formation, Athena, Redshift, Lambda, IAM, CloudWatch. • Proficiency in PySpark, Python, DBT, Airflow, Docker and SQL. • Deep understanding of data modeling techniques and best practices. • Experience with CI/CD tools and version control systems like Git. • Familiarity with More ❯

predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science) Experience of WTW's Radar and Emblem software is preferred Proficient at communicating results in More ❯

someone who enjoys building scalable data solutions while staying close to business impact. The Role As a Data Analytics Engineer , youll design, build, and maintain reliable data pipelinesprimarily using PySpark, SQL, and Python to ensure business teams (analysts, product managers, finance, operations) have access to well-modeled, actionable data. Youll work closely with stakeholders to translate business needs into … spend more time coding, managing data infrastructure, and ensuring pipeline reliability. Who Were Looking For Data Analytics : Analysts who have strong experience building and maintaining data pipelines (particularly in PySpark/SQL ) and want to work on production-grade infrastructure. Data Engineering : Engineers who want to work more closely with business stakeholders and enable analytics-ready data solutions. Analytics … Professionals who already operate in this hybrid space, with proven expertise across big data environments, data modeling, and business-facing delivery. Key Skills & Experience Strong hands-on experience with PySpark, SQL, and Python Proven track record of building and maintaining data pipelines Ability to translate business requirements into robust data models and solutions Experience with data validation, quality checks More ❯