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- Tasks: Design and build high-performance analytics infrastructure for a cutting-edge hospitality SaaS platform.
- Company: Join a scaling startup revolutionising the hospitality industry with real data solutions.
- Benefits: Remote work flexibility, competitive salary, and opportunities for professional growth.
- Why this job: Make a significant impact by optimising data systems and driving innovation in analytics.
- Qualifications: Strong experience in data engineering, advanced SQL skills, and familiarity with OLAP databases.
- Other info: Collaborative environment with a focus on data governance and quality standards.
The predicted salary is between 36000 - 60000 £ per year.
Are you a Senior Data Engineer who wants to join a scaling SaaS startup that is just about to close its Series A? A hospitality SaaS company is shaking up the industry, building a modern platform designed around real data. Remote in UK or Europe.
Tech Stack: Angular, TypeScript, Liveview, Tailwind, Elixir, Node, Nest, Postgres, GraphQL, Git, Kubernetes, Websockets, AWS.
Today the platform already processes a large volume of transactional information and has a strong data foundation in place:
- 500GB of structured transaction data
- 100M+ transactions across multiple restaurant types
- A data platform ready to scale
The next step is turning this into a high-performance analytics and data infrastructure that powers benchmarking, product insights and machine learning. We are looking for a Senior Data Engineer who can design and build the analytics architecture that sits alongside the transactional platform and unlocks the value of this data.
You will design and build the analytics infrastructure that powers data across the business. This includes building scalable pipelines, selecting and implementing the right warehouse architecture and ensuring analytical queries can run in seconds across hundreds of millions of records. You will work closely with engineers, data scientists and ML engineers to ensure the platform supports both product intelligence and machine learning use cases. This is a hands-on role where you will own the architecture, pipelines and performance of the analytics stack.
Responsibilities include:
- Build and optimise an OLAP analytics stack separate from the transactional database
- Design and maintain ETL / ELT pipelines moving data from transactional systems into the analytics warehouse
- Ensure data integrity across 100M+ transaction records
- Optimise analytical queries to deliver sub-second or few-second performance
- Implement monitoring, alerting and testing across data pipelines
- Support data modelling and suggest improvements to existing database structures
- Manage supporting infrastructure across the data platform
- Work closely with ML engineers to support model training and inference
- Collaborate with technical and non-technical stakeholders to turn business questions into efficient data models
- Contribute to the long term data architecture strategy
- Help establish data governance, consistency and quality standards across the platform
Requirements:
- Strong experience as a Senior Data Engineer
- Advanced SQL skills and strong query optimisation experience
- Experience building large scale analytics systems
- Hands-on experience with OLAP databases such as ClickHouse, Snowflake or Amazon Redshift
- Experience implementing caching strategies using Redis or AWS ElastiCache
- Strong knowledge of AWS infrastructure
- Experience building benchmarking or BI platforms
- Familiarity with orchestration tools such as Airflow, Kafka or AWS Glue
- Knowledge of partitioning and sorting strategies for large datasets
- Understanding of data science concepts such as clustering or recommendation
Additional tasks include selecting the appropriate analytics warehouse based on performance, cost and scalability, designing and deploying ETL / ELT pipelines ingesting data from Amazon Aurora into the analytics warehouse, implementing monitoring and alerting across pipelines and warehouse infrastructure, and evaluating the current data architecture and recommending improvements to support long term scale.
Senior Engineer, Data Engineering employer: AG Talent
Contact Detail:
AG Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Engineer, Data Engineering
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data engineering. This is your chance to demonstrate your expertise in building scalable analytics systems and optimising queries.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with OLAP databases, ETL pipelines, and AWS infrastructure. Practice common interview questions and think about how you can relate your past work to the role.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight your relevant experience and how you can contribute to our mission of building a modern data platform.
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with OLAP databases, ETL/ELT pipelines, and any relevant projects that showcase your skills in building scalable analytics systems.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about joining our hospitality SaaS company and how your background aligns with our mission to build a modern data platform.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Mention your advanced SQL skills, experience with AWS infrastructure, and any hands-on work with tools like Airflow or Kafka. We want to see what you can bring to the table!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at AG Talent
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, like Angular, TypeScript, and AWS. Be ready to discuss your hands-on experience with these tools and how you've used them to build scalable data solutions.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data engineering challenges in the past. Highlight specific projects where you designed ETL pipelines or optimised analytical queries, and be ready to explain your thought process.
✨Understand the Business Impact
Research the hospitality industry and think about how data engineering can drive insights and improve operations. Be prepared to discuss how your work can contribute to business goals, especially in terms of benchmarking and product intelligence.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data architecture strategy and their plans for scaling. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.