At a Glance
- Tasks: Transform analytics infrastructure into a modern Azure-based data platform with DevOps at its core.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Enjoy flexible remote work, competitive salary, and opportunities for professional growth.
- Other info: Be a senior technical lead in a dynamic team with excellent career advancement potential.
- Why this job: Shape the future of data platforms and drive impactful business decisions.
- Qualifications: 5+ years in data engineering with expertise in Azure and DevOps methodologies.
The predicted salary is between 70000 - 90000 € per year.
About the Role
We’re seeking a Senior Data Engineer to transform our analytics infrastructure from monolithic SQL/PostgreSQL systems into a modern Azure-based data platform with DevOps at its core. This permanent position focuses on building an automated, self-service architecture designed for continuous evolution. You’ll bring 5+ years of data engineering experience with proven expertise in implementing enterprise-scale data platforms and DevOps methodologies. You’ll architect solutions using modern patterns, establish automated data pipelines with CI/CD practices, implement infrastructure-as-code, and mentor our team while building systems that adapt to emerging technologies. We need someone who prioritises maintainable, scalable, and adaptable systems. We’re committed to Azure but flexible on specific products – we value pragmatic solutions based on actual needs.
Structure & Expectations
- Reports to: Product organisation – you’ll work closely with product teams to align data capabilities with business objectives
- Location: London office 3 days per week, flexible remote work the rest of the time
- Team: You’ll be the senior technical lead and engineer for data platform initiatives, working with business analysts, engineers, and product stakeholders
- Timeline: Initial focus on migration (6 months), then platform evolution, DevOps maturity, and capability expansion
Core Technical Requirements
- Azure Data Platform Architecture
- Microsoft Azure data stack expertise: ADF, Delta Lake, ADLS Gen2, Synapse, Databricks (with flexibility to integrate non-Microsoft solutions)
- Experience with PostgreSQL and SQL Server, including data replication/integration patterns for migration
- Dimensional and relational data modeling expertise
- Medallion architecture implementation (bronze→silver→gold)
- Data Engineering & Pipelines
- Proficiency in Python and SQL for ELT/ETL pipelines
- Batch, streaming, and micro-batching architectures
- CDC patterns and incremental load strategies at scale
- Experience with Delta Change Data Feed or equivalent real-time sync mechanisms
- Experience building ingestion pipelines from diverse external APIs (CRM, analytics, finance, observability tools) into a unified lakehouse
- DevOps & Infrastructure
- Infrastructure as Code (Terraform preferred)
- CI/CD with Azure DevOps or GitHub Actions
- Test automation for data pipelines (unit, integration, regression)
- Azure networking and security best practices
- Container orchestration (Kubernetes/AKS) experience beneficial
- Event-driven architectures and API integration patterns
- Monitoring and alerting with Azure Monitor and Log Analytics
- Performance tuning and cost optimisation
- Git version control proficiency
- Governance, Compliance & Security
- Strong understanding of information security requirements
- Experience with Microsoft Purview or similar governance frameworks
- GDPR/data protection implementation, including the right-to-be-forgotten
- RBAC, encryption strategies, and audit logging
- Data lineage and quality enforcement
Non-Technical Requirements
- Communication & Documentation
- Strong technical writing – please provide examples
- Clear presentation skills for technical and non-technical audiences
- Experience creating architecture diagrams, data flows, and runbooks
- Leadership
- Track record of training and upskilling teams
- Experience with structured project planning: from high-level initiatives through quarterly planning to executable tasks
- Comfort working with product managers and translating between technical and business contexts
What You’ll Do
- Architect a modern data platform with DevOps principles for long-term business evolution
- Establish automated engineering best practices for data, governance, and operations
- Build robust batch and real-time processing pipelines (integrating web application data with analytics sources and external APIs)
- Create comprehensive documentation and training materials
- Translate business requirements into maintainable technical solutions
- Mentor team members and drive continuous improvement
Why This Matters
You'll establish the foundation for our data platform's next decade. This platform will power our next generation of internal and customer products while empowering our business with real-time insights for faster, smarter decisions.
Senior Data Engineer: Data Platform DevOps & Architecture in London employer: Edgefolio Group
Join a forward-thinking company that prioritises innovation and employee development in the heart of London. As a Senior Data Engineer, you'll not only lead the transformation of our data infrastructure but also enjoy a flexible work environment that fosters collaboration and growth. With a commitment to modern technologies and a culture that values mentorship and continuous improvement, this role offers a unique opportunity to shape the future of our analytics capabilities while advancing your career in a supportive setting.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer: Data Platform DevOps & Architecture in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Azure. A friendly chat can lead to insider info about job openings or even referrals that could give you a leg up.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure Data Platform and DevOps practices. This will not only impress potential employers but also give them a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with CI/CD, data pipelines, and mentoring teams. Practice common interview questions and have examples ready to demonstrate your expertise.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team and contributing to our data platform evolution.
We think you need these skills to ace Senior Data Engineer: Data Platform DevOps & Architecture in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the specific skills and experiences mentioned in the job description. Highlight your expertise in Azure, data engineering, and DevOps methodologies to show us you’re the perfect fit for the role.
Showcase Your Projects:Include examples of past projects where you've implemented enterprise-scale data platforms or automated data pipelines. We love seeing real-world applications of your skills, so don’t hold back on the details!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re excited about this role and how your background aligns with our mission. This is your chance to show off your personality and passion for data engineering!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Edgefolio Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in the Azure data stack and the specific tools mentioned in the job description, like ADF, Delta Lake, and Databricks. Brush up on your SQL and Python skills too, as you'll likely be asked to demonstrate your proficiency in these areas.
✨Showcase Your DevOps Experience
Be prepared to discuss your experience with CI/CD practices and Infrastructure as Code, particularly with Terraform. Have examples ready that illustrate how you've implemented these methodologies in past projects, especially in relation to data pipelines.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in data engineering and how you’ve overcome them, particularly in building scalable and maintainable systems.
✨Communicate Clearly and Confidently
Since this role involves mentoring and working closely with product teams, practice explaining complex technical concepts in simple terms. Prepare to share examples of how you've successfully communicated with both technical and non-technical stakeholders in the past.
