10 of 10 ETL Jobs in Peterborough

experience using cloud-native data services, specifically in Microsoft Azure, Fabric, Dataverse, Synapse, Data Lake, Purview. Deep expertise in data engineering tools and practices, including Python, SQL, and modern ETL/ELT frameworks (e.g., Azure Data Factory, Talend, dbt). Experience designing and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL More ❯

stakeholders to identify data requirements and deliver sustainable solutions. Monitor and troubleshoot data pipeline issues to maintain data integrity and accuracy. Assist in the development, maintenance, and optimization of ETL (Extract, Transform, Load) processes for efficiency and reliability. Project & Improvement: Assist in gathering, documenting, and managing data engineering requirements and workflows. Contribute to the development of guidelines and documentation for … to data infrastructure. Participate in quality reviews of designs, prototypes, and other work products to ensure requirements are met. Skills & Experience: Basic understanding of data engineering concepts, such as ETL processes, data pipelines, and data quality management. Hands-on experience with SQL (e.g., writing queries, basic database management). Familiarity with data tools and platforms (e.g., Python, Power BI, Tableau More ❯

these creators and provide them access to social media opportunities. Job Description: As a Lead Data Scientist at Luupli, you will leverage AWS analytics services to analyze data and extract insights. You will collaborate with data engineers, product managers, and stakeholders to develop data-driven solutions and recommendations. Your expertise will shape our data strategy and support business growth. Responsibilities … to understand business goals, data needs, and analytics objectives. Develop data analysis strategies using AWS services like Amazon Redshift, Athena, EMR, and QuickSight. Design and build data pipelines and ETL processes for data extraction, transformation, and loading into AWS. Apply statistical and machine learning techniques for predictive and segmentation analyses. Identify key metrics, develop KPIs, and create dashboards with Amazon … Statistics, Mathematics, or related field. Experience as a Data Scientist, especially with AWS analytics services. Proficiency in AWS tools like Redshift, Athena, EMR, and QuickSight. Knowledge of data modeling, ETL, and data warehousing concepts. Skills in statistical analysis, data mining, and machine learning. Programming skills in Python, R, or Scala. Experience with SQL, NoSQL, visualization tools, and statistical packages. Strong More ❯

skills to liaise with technical and non-technical stakeholders. Experience working with diverse teams. Knowledge of Microsoft Azure and managing servers/virtual environments. Experience with BI tools, SQL, ETL, and data modelling. Knowledge of Tableau tools like RMT and Content Migration Tool. Familiarity with Azure DevOps CI/CD processes. Proficiency in HTML and CSS. Responsibilities include: Administer, optimize More ❯

Skills: - 5+ years in a business/data analyst role, ideally in a consultancy or commercial setting. - Strong analytical, problem-solving, and communication skills. - Experience with operational data processes, ETL, data warehouse migration, schema mapping, and MI/BI reporting. - Proficient in tools such as JIRA, Confluence, Asana, Miro, and Excel. - Familiarity with Agile (SCRUM), and ability to manage multiple More ❯

agile teams, and want to shape something from the ground up — this is for you. What you’ll do: Design and build a cloud-native data warehouse Develop scalable ETL/ELT pipelines and dimensional models (Kimball, Data Vault, etc.) Ensure high data quality, performance and reliability Collaborate with engineers, analysts and product teams Lead best practices and mentor others More ❯

technical requirements, data flows, and data formats. Experience creating functional and design specifications for platform architecture, data pipelines, and/or parser functionality. Familiarity with data integration techniques and ETL processes. Basic proficiency with scripting languages (e.g., Python) and data transformation tools. Understanding of RESTful APIs and data exchange formats (e.g., JSON, XML). Proven ability to work cross-functionally More ❯

continued scaling and optimisation of these. Their ideal candidate would have 10+ years experience in Data Engineering/Architecture and have good knowledge within: Data Warehousing (Snowflake, Redshift, BigQuery) ETL (Data Fabric, Data Mesh) DevOps (IaC, CI/CD, Containers) Leadership/Line Management Consulting/Client Facing Experience In return they would be offering Free Certification Scheme (ServiceNow, TOGAF More ❯

architecture, pipelines, and reporting solutions from the ground up. What You’ll Be Doing: Designing, building, and optimising scalable data pipelines, data warehouse structures, and integration processes. Implementing robust ETL solutions to consolidate data from multiple sources into the central data warehouse. Working with a fully cloud-based Azure ecosystem (including Azure Data Factory and Databricks). Exploring opportunities to More ❯

requirements. Key Responsibilities Collaborate with business team to understand migration requirements, including data prioritization, categorization, and compliance needs. Analyze existing data structures and workflows within Caliber QMS, Trackwise, and SoftXpert. Extract, transform, and load (ETL) data from legacy systems to Veeva Quality Vault while preserving data accuracy and integrity. Execute hands-on data migration tasks, including extraction, cleaning, and importing … team members in new processes and tools related to data migration and management. Required Qualifications Hands-on expertise with Caliber QMS, Trackwise, SoftXpert, and Veeva Quality Vault. Proficiency in ETL tools and techniques. Strong understanding of regulatory and data compliance standards in quality management. Excellent problem-solving skills. Effective communication skills to collaborate with cross-functional teams. Technical Proficiency: Expertise More ❯