At a Glance
- Tasks: Lead the development of our data lakehouse and transform data into revenue-generating products.
- Company: Join Alto Software Group, a key player in UK housing transactions with a start-up mindset.
- Benefits: Enjoy flexible working, 25 days leave, and a range of health and wellness perks.
- Other info: Collaborative culture with opportunities for career growth and personal development.
- Why this job: Make impactful decisions on critical infrastructure and shape the future of data at Alto.
- Qualifications: Experience in data platforms, Python, AWS, and modern data tools like Databricks.
The predicted salary is between 63000 - 77000 £ per year.
London | Hybrid — 2 days per week in our London HQ | Full-time
Alto Software Group is a B2B SaaS 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 start-up, we have a start-up mindset and want our people to operate with this mindset so that we can achieve our ambitions.
What You’ll Do
- Own the reliability and performance of our data lakehouse as it scales, taking the lead on the operational problems that don’t have an obvious answer.
- Build the infrastructure and business logic behind our data commercialisation products, partnering with product and commercial teams to turn data into revenue.
- Design 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.
- Lead the data side of modernising our legacy monolithic SQL Server database: extracting into the lakehouse and parallel data stores, introducing retention policies, and migrating to modern SQL frameworks.
- Write and optimise ETL processes and contribute to data modelling for both internal analytics and external-facing data products.
- Take work from ambiguous problem statements through design, build and deployment, and stay accountable for it in production.
- Raise the technical bar on how we build — reviewing designs, challenging decisions, and improving our engineering practices as you go.
What You Need to Be Successful
- Deep, hands‑on experience building and running production data platforms and products.
- A good level of experience in Python (particularly pyspark) for building data pipelines.
- Strong AWS and Terraform experience, with infrastructure-as-code as your default way of working.
- Substantial experience with a modern lakehouse or warehouse platform — Databricks ideally, or Snowflake/BigQuery.
- Real production experience with Fivetran, dbt, or equivalent ingestion and transformation tooling.
- Kafka or similar streaming systems in production, and the judgement to know when event‑driven is the right answer and when it isn’t.
- Strong SQL and sound data modelling instincts, plus experience working with large legacy relational estates.
- Comfort with container orchestration (ECS, Kubernetes) and how data workloads actually behave in production.
- A platform mindset — you take as much satisfaction from the paved road as from the pipeline that runs on it.
Our Technology Stack
- Data Platform: Databricks, dbt, Fivetran
- Languages: Python, SQL
- Databases: SQL Server (legacy, being modernised), plus lakehouse storage on S3
- Cloud & Infrastructure: AWS (EventBridge, Kinesis, Lambda, S3, EC2), Terraform (Infrastructure as Code)
- Streaming: Kafka
- Containers & Orchestration: ECS, Kubernetes
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.
Why Join Alto?
- This role offers genuine ownership of a platform at the point where it stops being a project and starts being critical infrastructure.
- You will have the autonomy to shape how data is built and consumed across the business.
- With the Databricks migration in flight and data products moving from idea to roadmap, this is the moment where the hardest and most interesting work sits.
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.
Senior Data Platform Engineer (AWS, Databricks) employer: Alto
Palo Alto Networks is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. Employees benefit from extensive growth opportunities through mentorship and involvement in cutting-edge SOC modernization projects, while enjoying a supportive environment that values diversity and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Senior 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!
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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.
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We think you need these skills to ace Senior 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!
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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.
