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Data Platform Engineer - (AWS, Databricks)

Alto
CompanyAlto
CategoryEngineering
LocationLondon
RemoteOn-site (inferred)
EmploymentFull-time
LevelNot stated
SalaryNot stated by the employer
Posted15 May 2026
Last verified30 Jul 2026
SourceEmployer career page (workable)
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Description
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 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 (EventBridge, 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/BigQuery), 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
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