At a Glance
- Tasks: Design and build data pipelines using Azure and PySpark in the CPG domain.
- Company: Fractal Analytics, a strategic AI partner for Fortune 500 companies.
- Benefits: Great workplace culture, career growth, and opportunities to work with cutting-edge technology.
- Other info: Collaborative environment with a focus on innovation and personal development.
- Why this job: Join a team that empowers imagination with intelligence and drives impactful decisions.
- Qualifications: Experience in data engineering and CPG domain is essential.
The predicted salary is between 70000 - 90000 € per year.
It has come to our notice that Fractal Analytics’ name and logo are being misused by certain unscrupulous persons masquerading as Fractal’s authorized representatives to approach job seekers to part with sensitive personal information and/or money in exchange of promise of lucrative job offers in Fractal. Please exercise caution and verify that the person approaching you is a genuine representative of Fractal Analytics, or an authorized consultant, before you provide any personal details or other non-public information.
Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work(R) Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.
Location: London
Core Technical Responsibilities
- CPG domain experience is mandatory
- Design and build end-to-end data pipelines (batch and near real-time) using PySpark, Databricks, and Azure Data Platform (ADF, ADLS, Synapse)
- Be hands-on in development, debugging, optimization, and production support of data pipelines
- Work with or extend existing/proprietary ETL frameworks (e.g., Mar's Simpel or similar) and improve performance and reliability
- Implement data modeling, transformation, and orchestration patterns aligned with best practices
- Apply data engineering fundamentals including partitioning, indexing, caching, cost optimization, and performance tuning
- Collaborate with upstream and downstream teams to ensure data quality, reliability, and SLAs
Architecture & Design
- Contribute to the design of cloud-native data architectures covering ingestion, processing, storage, and consumption
- Translate business and analytical requirements into practical, scalable data solutions
- Support data governance practices including metadata, lineage, data quality checks, and access controls
- Work within hybrid environments (on-prem to cloud) and support modernization initiatives
- Understand and apply data mesh concepts where relevant (domain ownership, reusable data products, basic contracts)
- Evaluate tools and frameworks with a build vs. buy mindset, recommending pragmatic solutions
Team & Delivery Responsibilities
- Act as a technical anchor for a data engineering team
- Provide technical guidance, code reviews, and mentoring to engineers
- Own delivery for assigned data products or pipelines — from design through deployment
- Collaborate with product owners, analysts, and architects to clarify requirements and priorities
Stakeholder & Communication
- Engage with business and analytics stakeholders to understand data needs and translate them into technical solutions
- Clearly communicate technical designs and trade-offs to both technical and non-technical audiences
- Escalate risks and propose mitigation strategies proactively
- Support documentation of architecture, pipelines, and operational processes
Good to Have
- Exposure to AI/ML data workflows (feature engineering, model inputs, MLOps basics)
- Awareness of LLMs / Agentic AI architectures from a data platform perspective
- Experience with other platforms such as AWS, GCP, Snowflake, BigQuery, Redshift
- Familiarity with data governance or catalog tools (DataHub, Collibra, dbt, etc.)
- Experience working in CPG, Retail, Supply Chain, or similar domains
If you like wild growth and working with happy, enthusiastic over-achievers, you will enjoy your career with us!
Senior Data Architect - Azure / CPG Industry in London employer: Fractal
Fractal Analytics is an exceptional employer that fosters a vibrant work culture where creativity and innovation thrive. Located in London, we offer our employees the opportunity to work with cutting-edge technology in the CPG domain while being part of a team that values passion and customer focus. With a commitment to employee growth and recognition as a Great Place to Work, Fractal provides a supportive environment for professional development and meaningful contributions to Fortune 500 companies.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Architect - Azure / CPG Industry in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work at Fractal or similar companies. A friendly chat can sometimes lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding the CPG domain. We recommend practising common interview questions and scenarios related to data architecture and Azure to show you're the right fit.
✨Tip Number 3
Don’t forget to showcase your passion for data and innovation during interviews. Share examples of how you've empowered imagination with intelligence in your previous roles – it’s all about making that connection!
✨Tip Number 4
Apply through our website for the best chance of landing that dream job! It’s the most direct route to get noticed by our hiring team, and we love seeing candidates who take that extra step.
We think you need these skills to ace Senior Data Architect - Azure / CPG Industry in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Architect role. Highlight your experience in the CPG domain and any relevant Azure projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data architecture and how you can contribute to our mission at Fractal. Keep it engaging and personal, so we get a sense of who you are.
Showcase Your Technical Skills:Don’t forget to highlight your technical expertise! Mention specific tools and frameworks you’ve used, like PySpark or Databricks, and any experience with data governance practices. We love seeing candidates who are hands-on and ready to dive into the tech!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at Fractal
✨Know Your Stuff
Make sure you brush up on your knowledge of Azure and the CPG industry. Be ready to discuss specific projects you've worked on, especially those involving data pipelines and cloud-native architectures. This will show that you’re not just familiar with the concepts but have practical experience.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled challenges in data engineering. Whether it’s optimising a data pipeline or ensuring data quality, having concrete examples will demonstrate your ability to think critically and act decisively.
✨Communicate Clearly
Practice explaining technical concepts in simple terms. You’ll likely need to communicate with both technical and non-technical stakeholders, so being able to articulate your ideas clearly is key. Think about how you can convey complex designs and trade-offs effectively.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy and how they approach data governance. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals. Plus, it gives you a chance to engage with your interviewers!
