26 to 50 of 121 ETL Jobs in the Thames Valley

or GCP). Snowflake Expertise: Strong practical experience with Snowflake components (Snowpipe, Snowpark, Tasks, Dynamic Tables, UDFs). SnowPro certification preferred. Technical Proficiency: Advanced Python and SQL skills for ETL/ELT workflows and data transformations. Cloud & Automation: Familiarity with CI/CD pipelines and automated testing for data workflows. Governance & Security: Understanding of data governance frameworks and security best More ❯

learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience More ❯

Domain is a must. Under 7 years of experience only. Permanent. Key Responsibilities Design, develop, and maintain data ingestion pipelines using open-source frameworks and tools Build and optimise ETL/ELT processes to handle small to large-scale data processing requirements Develop data models and schemas that support analytics, business intelligence and product needs Monitor, troubleshoot, and optimise data More ❯

at least one of: Front Office (Sales & Trading), Risk Management, or Finance. Strong programming in Python, Java and SQL (Rust a plus). Proven experience building streaming and batch ETL/ELT pipelines at scale. Strong understanding of market/trade data lifecycles and time series concepts. Experience with AWS and cloud-native data services. Excellent communication and stakeholder management More ❯

and modelling teams with reliable, high-quality data. Expect to work across diverse client projects, collaborating with both internal engineers and client tech teams. Key responsibilities: Build and maintain ETL pipelines and cloud data warehouses (AWS, GCP, Snowflake) Develop custom data connectors (e.g. Salesforce, SAP) Automate data cleansing and transformation workflows Support analytics and AI teams with clean, production-ready More ❯

integrity. Skills & Experience Expertise in dimensional modelling and strong understanding of Third Normal Form data models. Demonstrated experience across conceptual, logical, and physical data architectures. Familiarity with data integration, ETL, and data transformation patterns. Hands-on experience with metadata architecture and master data management frameworks. Solid understanding of data governance, lineage, and stewardship concepts. Experience working with cloud data platforms More ❯

or integration engineering. Strong proficiency with AWS cloud-native services. Solid SQL skills and scripting experience (Python preferred). Expertise in data modelling and mapping complex transformations. Familiarity with ETL/ELT tools and streaming technologies (Kafka, Kinesis). Experience with CI/CD pipelines and infrastructure as code (Terraform or CloudFormation). Excellent communication skills – able to translate business More ❯

governance adoption. Experience establishing reference data management and data quality practices at enterprise scale. Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines. Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure). Experience with both transactional RDBMS and modern distributed/cloud-native databases. Familiarity with reporting and analytics More ❯

data engineering using Azure, Databricks, SQL, and Azure Data Factory, including medallion architecture. Proven leadership in guiding teams through complex data deliveries and adopting best practices. Strong background in ETL orchestration and hybrid cloud integration. Hands-on experience with Power BI and DAX, building dashboards that drive actionable insights. Excellent communication skills, with the ability to translate technical concepts into More ❯

processes (batch and streaming) from diverse sources Collaborate with AI engineers and product teams to define data requirements and integrate pipelines seamlessly with models and applications. Build and maintain ETL/ELT processes that ensure data integrity, consistency, and accuracy across systems. Optimize data infrastructure for performance, cost efficiency, and scalability in cloud environments. Develop and manage graph-based data More ❯

for data analysis and validation. Experience in data architecture principles and data governance. Solid understanding of Insurance domain concepts (Specialized Insurance, London Market, Regulatory Data). Preferred Experience with ETL tools and data integration processes. Familiarity with data warehousing concepts and cloud data platforms. Exposure to Fivetran, SSIS, or Snowflake advanced features. Personal Besides the professional qualifications of the candidates More ❯

work closely with the Director of Analytics and Strategic Data Manager and be responsible for implementing data pipelines in Azure Data Factory and Azyre Databricks, supporting Darewhaoure implementation and ETL process. Location: Hybrid in London Salary: £55,000 to £65,000 + Benefits To be considered: Minimum 3 years of experience working as a Data Engineer within an Azure Environment. More ❯

Key Responsibilities:- Design, develop, and maintain scalable data pipelines and ETL processes. Collaborate with data analysts and business stakeholders to understand data requirements. Optimize data workflows for performance and reliability. Ensure data quality, integrity, and security across systems. Work with large datasets using tools like Hadoop, Spark, and SAS. Integrate data from various sources including IBM Mainframe systems. Troubleshoot and More ❯

the business. What We're Looking For Proven experience leading BI or analytics functions (ideally in tech, SaaS, or payments). Strong technical skills in SQL, data modelling, and ETL . Proficiency with BI tools such as Power BI, Tableau, or Looker. Excellent communication and stakeholder management skills. Strategic thinker with hands-on delivery experience. The client is looking to More ❯

vision and roadmap that supports the evolving needs of capital markets firms. Skills Required Technical Expertise: Proficiency in data modelling, database design, SQL, Python, Kafka(optional), and experience with ETL tools and cloud data platforms. Data Management : Strong knowledge of data warehousing solutions. Capital Markets Knowledge: Understanding of the specific data requirements, challenges, and regulatory landscape within the capital markets More ❯

ability to translate business needs into smart, scalable solutions. • Proven experience with Microsoft 365 and Power Platform (PowerApps, PowerAutomate, Dataverse) • Strong SQL skills, including data modeling, performance tuning, and ETL processes • Hands-on experience with SharePoint, Teams, and Exchange integration • Experience with Azure DevOps, API integration, and application lifecycle management • Excellent communication skills with the confidence to engage technical and More ❯

degree in Mathematics, Computer Science, Engineering, or a related discipline. Strong proficiency in SQL and Python (or another object-oriented programming language). Demonstrated experience in designing and managing ETL/ELT pipelines. Exceptional attention to detail, with a focus on data accuracy and process reliability. A proactive problem-solver with strong analytical and communication skills, capable of working both More ❯

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., OBJ, FBX, glTF), point clouds, and large-scale computer vision datasets-or the ability to quickly upskill in 3D data workflows. More ❯

data structures, algorithms, and programming principles. •Experience working with other relevant languages such as Python, JavaScript, or TypeScript. • Data Systems Knowledge: •Exposure to working in data-centric environments, supporting ETL/ELT pipelines or data processing services. •Familiarity with SQL and NoSQL databases. •Understanding of data privacy and security concepts. • Ways of Working: •Comfortable working in Agile/Scrum environments More ❯

Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm). Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing. Ability to design scalable, secure, and observable systems in fast-moving environments. Strong debugging and problem-solving skills across distributed More ❯

Familiarity with distributed system patterns and architectural trade-offs. Experience with performance tuning and troubleshooting in complex environments. Data Systems Knowledge: Exposure to working in data-centric environments, supporting ETL/ELT pipelines or data processing services. Familiarity with SQL and NoSQL databases. Understanding of data privacy and security concepts. Tooling & Infrastructure: Experience with CI/CD pipelines, containerization (Docker More ❯

Familiarity with distributed system patterns and architectural trade-offs. Experience with performance tuning and troubleshooting in complex environments. Data Systems Knowledge: Exposure to working in data-centric environments, supporting ETL/ELT pipelines or data processing services. Familiarity with SQL and NoSQL databases. Understanding of data privacy and security concepts. Tooling & Infrastructure: Experience with CI/CD pipelines, containerization (Docker More ❯

understanding and command of Data Pipelines Excellent communication skills Flexible approach towards hybrid working when required Nice to have: Exposure to Microsoft Fabric Experience in large Data Migration projects (ETL) Immediate availability Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept More ❯

GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. More ❯

various data modelling techniques and tools. Deep understanding of different data storage solutions (e.g., relational, NoSQL, data lakes) and their appropriate use cases. Strong knowledge of data integration patterns, ETL/ELT processes, and data pipeline orchestration. Experience with AWS data platforms and their respective data services. Solid understanding of data governance principles, including data quality, metadata management, and access More ❯