At a Glance
- Tasks: Join us to scale our data lakehouse and build innovative data solutions.
- Company: Alto Software Group, a fast-growing B2B SaaS company transforming UK housing transactions.
- Benefits: Enjoy hybrid work, 25 days leave, and a range of wellness perks.
- Other info: We're committed to diversity and welcome applicants from all backgrounds.
- Why this job: Make a real impact in a dynamic environment with exciting growth opportunities.
- Qualifications: Strong Python skills and experience with AWS and data infrastructure.
The predicted salary is between 60000 - 80000 £ per year.
Alto Software Group is a B2B Saa S company that powers more than half of all UK housing transactions each year.
We create software solutions that connect businesses and consumers, delivering a one‑stop shop for estate agents and home builders.
Our goal is to drive efficiency, speed up transactions, reduce risk, and improve the end‑customer experience.
While we’re not a startup, we operate with a startup mindset.
We’re looking for people who share this mentality and are ready to tackle big ambitions.
This is a fast‑growing and exciting business going through significant change, and there’s never been a better time to join us.
We’re looking for a passionate Data Platform Engineer to join the Alto Team.
You’ll help us scale the data lakehouse that powers analytics and AI across the business, build the infrastructure behind new data commercialisation products, and create the reusable building blocks that let our engineering teams move data around safely and quickly.
- What You’ll Do
- Provide ongoing operational support and build new solutions for our data lakehouse and scale it out to serve internal analytics and AI use cases that boost productivity across the business.
- Build the infrastructure and business logic behind our new data commercialisation opportunities, partnering with product and commercial teams to turn data into revenue‑generating products.
- Design and build the abstractions, blueprints and reusable templates that let service and analytics teams work with data safely and consistently, from ingestion through to storage and access.
- Play a key role in modernising our legacy monolithic SQL Server database — extracting data into our lakehouse and other parallel data stores, introducing data retention policies, and helping migrate to modern SQL frameworks and languages.
- Write ETL processes and contribute to data modelling for both internal analytics and external‑facing data products, where the platform alone isn’t enough.
- Take ownership of your work from design to deployment, either independently or as part of a collaborative team.
- Help shape our engineering practices and explore new ways of working to deliver value to our internal customers in a fast, predictable way.
- Our Technology Stack
- We believe in using the right tool for the job. Our current stack includes:
- Data Platform: Databricks, DBT, Fivetran
- Languages: Python, SQL
- Databases: SQL Server (legacy, being modernised), plus lakehouse storage on S3
- Cloud & Infrastructure: AWS (Event Bridge, Kinesis, Lambda, S3, EC2), Terraform (Infrastructure as Code)
- Streaming: Kafka
- Containers & Orchestration: ECS, Kubernetes
- Who We’re Looking For
- A data or platform engineer with strong Python skills and a track record of building data infrastructure that other engineers and analysts depend on.
- Hands‑on experience with AWS and Terraform, and a comfort with infrastructure‑as‑code as the default way of working.
- Experience with a modern lakehouse or warehouse platform (Databricks ideally, or Snowflake/Big Query), and with data ingestion and transformation tools (Fivetran/DBT).
- Familiarity with Kafka or similar streaming systems, and an interest in building the abstractions that make event‑driven data flows easy for other teams to adopt.
- Solid SQL skills and a good sense for data modelling, even if it isn’t the main thing you do day to day.
- Awareness of container orchestration (ECS, Kubernetes) and how data workloads run in production.
- A platform mindset — you enjoy building tools, templates and paved roads for other engineers as much as you enjoy shipping pipelines yourself.
- Our Behaviours
- Explore Boldly: We value engineers who are eager to learn new technologies and stay current with industry trends.
- Bounce Back Stronger: A pragmatic problem‑solver who can navigate ambiguity and find simple solutions to complex challenges.
- Own It Together: A collaborative team member who is willing to share early‑stage work and both give and receive constructive feedback.
- Make It Happen: A person who takes pride in their delivery and is passionate about creating high‑quality software at pace.
- Know
- Our
Customers: You’re a platform engineer who is genuinely interested in your internal customers' perspective.
You strive to understand the purpose of your work so you can deliver the most impactful solutions.
Don’t worry if you don’t check every box!
We’re looking for passionate engineers who are excited to grow.
If you have a solid foundation in data engineering and are eager to learn, we encourage you to apply.
We are committed to building a diverse and inclusive team and welcome applications from all backgrounds.
Benefits
- Hybrid – 2 days per week in our London HQ for team collaboration
- Opportunities for career development and advancement within a growing organisation.
- Everyday Flex – greater flexibility over where and when you work
- 25 days annual leave + extra days for years of service
- Day off for volunteering & Digital detox day
- Festive Closure – business closed for period between Christmas and New Year
- Cycle to work and electric car schemes
- Free Calm App membership
- Enhanced Parental leave
- Fertility Treatment Financial Support
- Group Income Protection and private medical insurance
- Gym on‑site in London
- 7.5% pension contribution by the company
- Discretionary annual bonus up to 10% of base salary
- Talent referral bonus up to £5K
We want to make ASG more welcoming, fair and representative every day.
We’ll consider everyone who applies for this role in the same way, regardless of your ethnicity, colour, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, neurodiversity status, family or parental status, or how long you’ve spent unemployed.
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Data Platform Engineer - (AWS, Databricks) employer: Alto
Palo Alto Networks is an exceptional employer that fosters a culture of innovation and collaboration, where every employee's voice is valued. With a strong commitment to employee growth through immersive training programs like FLIGHT, team members are equipped to tackle real-world challenges in cybersecurity. The remote nature of the Major Account Manager role allows for flexibility while still enabling impactful contributions to a mission-driven company dedicated to protecting our digital way of life.
StudySmarter Expert Advice🤫
We think this is how you could land Data Platform Engineer - (AWS, Databricks)
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Alto!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Platform Engineer - (AWS, Databricks) at Alto.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Alto.
✨Apply Directly through Our Website
When you find a suitable opening like Data Platform Engineer - (AWS, Databricks) at Alto, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Platform Engineer - (AWS, Databricks)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Alto, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Alto. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Alto
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Alto!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
