City of London, London, United Kingdom Hybrid / WFH Options
Hexegic
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 ❯
on experience or strong interest in working with Foundry as a core platform Forward-Deployed Engineering – delivering real time solutions alongside users and stakeholders Broader Skillsets of Interest: Python & PySpark – for data engineering and workflow automation Platform Engineering – building and maintaining scalable, resilient infrastructure Cloud (AWS preferred) – deploying and managing services in secure environments Security Engineering & Access Control – designing More ❯
understanding of data integration, data quality, and data governance. Extensive experience in working with big data technology tools and platforms such as Microsoft Azure Data Factory, Databricks, Unity Catalog, PySpark, Power BI, Synapse, SQL Server, Cosmos Db, Python. Understanding and application of cloud architectures and microservices in big data solutions. Understanding of commodities industry. Rate/Duration 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 ❯
Azure Data Engineer - 1/2 days onsite Summary: Join a team building a modern Azure-based data platform. This hands-on engineering role involves designing and developing scalable, automated data pipelines using tools like Data Factory, Databricks, Synapse, and More ❯
Data Analyst (SQL, PySpark, Python) London - Hybrid (2 Days Onsite) Inside IR35 - Daily Rate Our client is seeking an experienced Data Analyst to support a key client engagement within their professional services division. This is an initial 1 year contract based in London , operating on a hybrid basis (2 days onsite per week) and falling inside IR35 . Key … Responsibilities: Independently manage data extraction, cleansing, and transformation activities Develop production-grade analytics code using SQL, PySpark, and Python Analyze large-scale datasets to generate actionable insights and visualizations Collaborate across technical and business teams to drive data-driven decision making Required Experience: 3–5 years' hands-on experience in data analysis, insight generation, and data visualization Proven expertise … in SQL and PySpark , with solid working knowledge of Python Background working with big data platforms , large datasets, and pipelines Strong analytical thinking and a collaborative, self-directed working style Experience in the Payments , FinTech , or financial services sector is highly desirable, though not mandatory More ❯
