Solve IT Consultant
Lead Analytics Engineer / Data Architect
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Lead Analytics Engineer / Data Architect
Location
London - Hybrid
Duration
6-12 Months
Experience
15+ Years
Role Summary
We are seeking an experienced Senior Data Analyst / Data Architect to lead the design, development, and optimization of enterprise-scale data platforms and analytical solutions. The ideal candidate will possess strong expertise in data modeling, cloud data warehousing, business analytics, and modern data engineering practices. This role requires close collaboration with business stakeholders, architects, analysts, and engineering teams to transform complex business requirements into scalable and performant analytical solutions.
Key Responsibilities
Data Architecture & Design
- Design and implement enterprise-grade data architectures supporting analytics, reporting, and AI/ML initiatives.
- Develop conceptual, logical, and physical data models aligned with business requirements.
- Establish scalable dimensional, semantic, and canonical data models for enterprise reporting.
- Define data standards, governance principles, and best practices across the data ecosystem.
- Lead architecture reviews and ensure adherence to enterprise architecture standards.
Analytics Engineering
- Build and maintain scalable, reusable, and modular data models using dbt and Snowflake.
- Transform legacy data assets and complex database views into optimized cloud-native analytical structures.
- Develop curated semantic layers to enable self-service analytics and business intelligence.
- Implement automation for data transformations, testing, deployment, and monitoring.
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.
Data Analysis & Business Insights
- Partner with business stakeholders to understand analytical requirements and define KPIs.
- Translate business problems into data solutions and actionable insights.
- Perform advanced analysis of large datasets and provide strategic recommendations.
- Support executive dashboards, operational reporting, and performance measurement frameworks.
- Drive data-driven decision making through high-quality analytical outputs.
Data Quality & Governance
- Define and implement data quality frameworks, validation rules, and monitoring processes.
- Establish metadata management, data cataloging, and lineage practices.
- Ensure compliance with data governance, security, privacy, and regulatory standards.
- Develop policies for master data management and data stewardship.
Performance Optimization
- Optimize Snowflake storage, compute resources, and warehouse configurations.
- Improve query performance, data loading processes, and reporting response times.
- Monitor platform utilization and recommend cost optimization strategies.
- Implement access controls, role-based security, and attribute-based access control (ABAC).
Leadership & Collaboration
- Mentor junior analysts, engineers, and data modelers.
- Lead technical workshops, design discussions, and architecture reviews.
- Collaborate with product owners, business users, data scientists, and engineering teams.
- Act as a trusted advisor for data strategy and modernization initiatives.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Technical Requirements
Core Platforms
- Expert-level experience with Snowflake Cloud Data Platform.
- Strong hands-on expertise in dbt Core and dbt Cloud.
- Experience with modern cloud platforms such as AWS, Azure, or GCP.
- Familiarity with data orchestration tools such as Airflow, Azure Data Factory, or AWS Glue.
Data Modeling Expertise
- Dimensional Modeling (Kimball Methodology).
- Semantic Layer Design and Business Metrics Modeling.
- Data Vault and Enterprise Data Warehouse concepts.
- Logical, Physical, and Canonical Data Modeling.
- Star Schema and Snowflake Schema design.
Analytics & BI
- Power BI, Tableau, Looker, or equivalent BI platforms.
- KPI framework development and executive dashboard design.
- Advanced SQL and analytical problem-solving.
- Business requirements gathering and stakeholder management.
Data Engineering
- ETL/ELT design and implementation.
- Data pipeline development and optimization.
- Data quality validation and automated testing.
- Batch and near real-time data processing concepts.
Software Engineering Practices
- Git-based source control and branching strategies.
- CI/CD pipeline implementation.
- Automated testing frameworks.
- Agile and DevOps methodologies.
- Infrastructure-as-Code knowledge is a plus.
“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