Top Analytics Engineer Jobs in London

Develop and optimize data processing systems using PySpark within a big data platform. Requires expertise in data engineering, modern data processing technology stacks, and experience with real-time and low-latency data processing.

Exciting opportunity for a Principal Data Engineer at Ogury to shape the future of their data platform, enable data-driven decisions, and maintain high data quality standards. The role involves defining the long-term vision, building and leading the data platform, implementing data solutions, mentoring team members, and promoting data engineering best practices.

Checkout.com is seeking a Senior Data Platform Engineer to join their Data Platform Team. The team's focus is on building a world-class data platform to power products and analytics, maximizing time for business problem-solving. Key responsibilities include building enablement components, developing documentation, automating workflows, staying updated on data engineering technologies, mentoring junior members, and fostering platform adoption.

Seeking a Data Engineer with extensive experience in SQL and ETL practices, with a focus on delivering data solutions and changes for the company. The role involves working collaboratively with various internal stakeholders and maintaining data integrity across systems.

As a Senior Data Engineer at BJSS, you will be responsible for building scalable and re-usable data solutions using software engineering best practices. You will work on deploying data pipelines and processes in a production-safe manner, utilizing a variety of technologies and tools in the cloud. The role involves collaborating with multi-disciplinary teams to deliver modern data platforms for large organizations.

Develop high performance and scalable solutions to extract, transform, and load big data. Design, build, test, deploy cutting-edge solutions at scale. Support People Data applications, ensure data quality, and interact with engineering teams. Implement data quality checks, validation, and cleaning processes.

Develop high performance and scalable solutions for extracting, transforming, and loading big data. Design and deploy cutting-edge solutions at scale to drive value from data at Walmart. Support People Data applications ensuring Data Quality and Governance standards. Collaborate with engineering teams globally to ensure data accuracy and quality.

As a Data Engineer in the WPP Enterprise Data Group, responsible for designing and implementing scalable data solutions. Focus on large-scale data ingestion, processing, storage/querying, streaming, and batch to ensure enterprise-scale data transformation. Work with a team of Data Engineers to deliver world-class solutions using key technologies like Databricks on Azure. Embrace a culture of lifelong learning and collaboration.

Aker Systems, a highly secure enterprise data platform provider, is seeking a Lead Data Engineer to work on solutions that acquire, process, and present data for clients. Responsibilities include coding and testing data pipelines, refining database design, expanding data platform capabilities, and conducting data analysis. The ideal candidate should have experience in data pipeline development, data modeling, Agile methodology, AWS services, Python programming, and Test Driven Development.

The Senior Data Engineer at LiveScore Group will be responsible for querying data sets, building data pipelines, analyzing customer data, generating insights, creating KPI dashboards, providing actionable insights to marketing teams, and developing data architecture solutions. This role requires expertise in SQL, Python, and Google Cloud Platform.

Seeking an experienced Senior Data Engineer to build, monitor, and automate data pipelines using the latest tools and frameworks. Responsibilities include designing and managing ingestion pipelines, optimizing data transformation processes, and leading the adoption of new technologies. Required skills include expertise in Scala, Python, Java, big data processing frameworks, cloud computing platforms, messaging platforms, and data structures.

Seeking a Senior Data Engineer to co-lead the Product Development team, with responsibilities including managing technical builds, approaches, and priorities. Must have experience in data engineering, media environments, and programming languages such as Python and SQL. Knowledge of ETL, serverless, and cloud computing is required.

Seeking a skilled Data Architect to build and own the Data acquisition strategy and delivery in a global organization. Responsibilities include designing and optimizing data pipelines, technologies, and patterns to feed data models for analytics solutions. Must have extensive experience in data architecture and cloud technologies such as Azure and GCP.

Ophelos is building software and AI products to help individuals and businesses manage debt in a more humane and efficient way. They are looking for talented Data professionals to join their team in the future.

AVEVA is seeking a Data Architect to work on customer, product, and people data domains, responsible for designing and managing data architecture to align with business objectives. This role involves strategic planning, designing data systems, implementing database management systems, defining technology strategies, and more. The Data Architect collaborates with stakeholders to ensure project delivery aligns with strategic roadmaps and simplifies existing data architecture.

As a Senior Data Engineer at Fospha, you will play a key role in designing, developing, and maintaining scalable data pipelines and architectures to support business initiatives. You will ensure data integrity, optimize data storage, and provide insights for strategic decision-making. Additionally, you will drive continuous improvement in data processes and promote a culture of data excellence.

As a Data Engineer at Walmart, you will be responsible for developing and maintaining data pipelines to support data science initiatives. You will work with a mammoth scale of data to create valuable data assets for retail analytics. Collaboration with Data Scientists, Analysts, and business stakeholders to solve complex challenges is crucial for evolving the retail business model.