SoTalent
Senior Data Warehouse Engineer
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior Data Warehouse Engineer
đź“Ť Location: United Kingdom (Hybrid)
🏢 Industry: Education
đź’Ľ Work Setting: Hybrid
Are you passionate about building scalable cloud data platforms, transforming complex data into actionable insights, and driving data-driven decision-making across an organization? We are seeking a Senior Data Warehouse Developer to design, develop, and optimize modern cloud-based data warehousing, integration, and analytics solutions that support enterprise reporting, business intelligence, and strategic initiatives.
In this role, you will be responsible for developing robust data architectures, managing large-scale data platforms, implementing data integration pipelines, and ensuring high standards of data quality, governance, security, and performance. You will work closely with business stakeholders, engineering teams, and analytics professionals to deliver innovative solutions that enable informed decision-making and operational excellence.
Key Responsibilities
- Design, develop, and maintain enterprise data warehouse, data lake, and business intelligence solutions.
- Build scalable, secure, and high-performance data architectures to support reporting, analytics, and operational requirements.
- Develop, optimize, and support data integration pipelines for extracting, transforming, and loading data from multiple internal and external sources.
- Design and implement data models, semantic layers, and analytical datasets to support business intelligence and reporting initiatives.
- Collaborate with stakeholders to understand business requirements and translate them into effective data solutions.
- Architect future-state data platforms and contribute to technology roadmaps and modernization initiatives.
- Monitor and troubleshoot data platform issues, ensuring reliability, accuracy, and performance.
- Develop and maintain data quality, governance, security, and lineage frameworks.
- Support enterprise analytics by delivering efficient reporting and visualization solutions.
- Partner with cross-functional teams to ensure successful delivery of data-driven initiatives.
- Implement configuration management, deployment processes, and quality assurance standards.
- Contribute to release planning, platform enhancements, and continuous improvement initiatives.
- Evaluate emerging technologies and recommend innovative solutions to improve data capabilities.
- Work closely with technical leadership throughout the product and data lifecycle.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Required Skills & Qualifications
- Strong experience across the complete lifecycle of Data Warehousing, Data Lakes, Business Intelligence, and Reporting solutions.
- Proven expertise in designing, developing, and managing large-scale enterprise data platforms.
- Strong SQL development, performance tuning, and data analysis skills.
- Experience with data modeling, ETL/ELT development, and large-scale data processing.
- Hands-on experience with cloud-based data platforms and modern data engineering practices.
- Experience developing and supporting data integration pipelines and workflow automation.
- Knowledge of data governance, data security, data quality management, metadata management, and data lineage.
- Experience working with business intelligence and data visualization platforms.
- Strong understanding of software development lifecycle methodologies including Agile, Iterative, and Waterfall approaches.
- Experience integrating APIs and external data sources into enterprise data ecosystems.
- Proficiency in Python, R, or similar technologies for advanced analytics and data processing.
- Experience with relational databases, NoSQL platforms, distributed data architectures, and high-availability systems.
- Familiarity with big data technologies, distributed processing frameworks, and cloud-native analytics solutions.
- Strong understanding of scalability, performance optimization, and enterprise-grade data architecture principles.
- Excellent problem-solving, communication, and stakeholder management skills.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Preferred Qualifications
- Experience working within Agile delivery frameworks and large-scale planning environments.
- Exposure to modern data platform technologies and next-generation analytics solutions.
- Experience with DataOps, automation, continuous integration, and data engineering best practices.
- Knowledge of artificial intelligence, machine learning, and advanced analytics ecosystems.
- Experience handling large datasets, cluster management, and performance optimization initiatives.
- Relevant certifications in Data Warehousing, Business Intelligence, Cloud Platforms, Data Engineering, or Analytics.
- Experience supporting reporting, compliance, regulatory, or education-focused data environments is advantageous.
Education
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
What Success Looks Like
- Delivering scalable, secure, and high-performing data solutions.
- Enabling business users with reliable analytics and actionable insights.
- Maintaining high standards of data quality, governance, and compliance.
- Driving innovation through modern cloud and data engineering technologies.
- Collaborating effectively across teams to deliver enterprise-wide data initiatives.
- Continuously improving data platform performance, reliability, and business value.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location