Lumora Analytics
Data Engineer
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Company Description
Lumora Analytics is a UK-based data and analytics consultancy focused on pharmaceutical commercial operations. The team designs and delivers bespoke data platforms, business intelligence solutions, automated reporting, and commercial analytics tailored to each client's needs. Instead of using off-the-shelf software, Lumora Analytics builds scalable solutions that connect fragmented data, automate manual processes, and turn complex information into clear, actionable insights. Their expertise includes enterprise data platforms, data warehousing, forecasting tools, KPI frameworks, dashboard development, and workflow optimization. The company partners with pharmaceutical organizations seeking to modernize reporting, build trusted data foundations, and improve commercial decision-making.
Role Description
This is a full-time, on-site Data Engineer role based in London. The Data Engineer will design, build, and maintain scalable data pipelines that support pharmaceutical commercial analytics and reporting. Day-to-day responsibilities include developing and optimizing ETL processes, modeling data for analytics and business intelligence, and managing data warehousing solutions to ensure reliability and performance. The role involves collaborating closely with consultants, analysts, and client stakeholders to understand requirements, integrate multiple data sources, and deliver well-structured datasets and dashboards. The Data Engineer will also contribute to improving data quality, governance, and documentation, and support the automation of reporting and forecasting workflows.
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Qualifications
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- Candidates should possess strong Data Engineering skills, including experience building and maintaining scalable data pipelines.
- Candidates should possess solid Data Modeling skills to design schemas and structures optimized for analytics and reporting.
- Candidates should possess hands-on experience with Extract Transform Load (ETL) processes and tools to integrate and transform data from multiple sources.
- Candidates should possess practical knowledge of Data Warehousing concepts and implementation, including performance optimization and data governance.
- Candidates should possess Data Analytics skills to support business intelligence, dashboard development, and insight generation.
- Proficiency with SQL and at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java).
- Experience working with cloud data platforms (e.g., AWS, Azure, or GCP) and related data services is highly beneficial.
- Familiarity with pharmaceutical or life sciences data and commercial operations is an advantage but not mandatory.
- Ability to collaborate with cross-functional teams, communicate technical concepts clearly, and document solutions thoroughly.
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.
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