Senior / Staff Data Engineer - Platform

Hello! 👋

Would you love to improve the way companies take care of their people, their most valuable asset? We are looking for a Senior/Staff Data Engineer to join Factorial Data Ops team and help us make data a first-class asset across our product.

Senior/Staff Data Engineer (Platform): What’s the mission?

• Our data platform already empowers data-driven features across Factorial by providing ingestion services (DBs, Events,SaaS APIs), storage capabilities (Data Lake, Stream Storage, Data Warehouse), processing engines, data quality, governance, and more.

• As a Senior/Staff Data Engineer, you’ll expand this mission by strengthening our analytics and platform capabilities, leveraging data engineering best practices to implement and maintain robust, scalable, and reliable data infrastructure.

• You will help make data a core asset for the Factorial product, building data infrastructure that not only supports internal analytics but also empowers our applications and customer-facing features.

• You will work closely with Product teams, Analytics Engineers and Infrastructure teams, ensuring reliability, performance, compliance, and high data quality in our Lakehouse architecture.

The role 📜

• You’ll be part of a small, high-agency data platform team, operating with a strong sense of ownership and autonomy.

• Despite being a small team, your work will have large impact, serving and collaborating with 150+ product developers and multiple product domains across Factorial.

• You will collaborate with Product, Analytics, and Platform teams to integrate data from various sources, design efficient data flows, facilitate data access and evolve our data platform capabilities.

• You’ll engage with stakeholders across the company, translating data, monitoring, and platform requirements into actionable technical initiatives that deliver long-term value.

Our stack & the day-to-day 🧑‍💻

• Regarding programming languages, we predominantly use Python to build custom data integrations, pipelines, and data-driven products. Additionally, we have developed our own Spark processing framework using Scala.

• You’ll own and evolve Lakehouse components, applying best practices across batch and streaming use cases using technologies such as Clickhouse, Apache Spark and Apache Flink.

• You’ll build data products and infrastructure that seamlessly integrate with Factorial’s core product, empowering both internal teams and customers with reliable, data-driven capabilities.

• You’ll play a key role in the infrastructure side of the data platform, designing, deploying, and operating data systems in close collaboration with the Infrastructure team.

• You’ll write RFCs, drive architectural decisions, and mentor other engineers, especially Analytics Engineers working within the Lakehouse framework.

• You’ll iterate in short development cycles, using ephemeral development environments to test and fail fast, under a GitOps mindset with CI/CD best practices.

Your first steps at Factorial

• Read a lot: Get to know Factorial’s product, customers, and current data platform and analytics practices.

• Learn a lot: Pair with engineers across domains to understand their data needs and how a strong data platform can empower both analytics and product features.

• Code a lot: Contribute to improvements across ingestion, processing, quality, governance, and data exposure layers.

• Fail a lot: We encourage experimentation and learning through iteration.

• Talk a lot: Participate in team rituals and stakeholder conversations to discover how data can better support our product and customers.

What we’d love to see in your background

• Solid experience building and operating reliable, scalable data systems, with a strong focus on analytics transformation and Lakehouse best practices. As a senior data engineering role, we expect you to have the ability to dive deep into the inner workings of data engines and components, understanding their architecture and details to build more efficient and scalable solutions.

• Hands-on experience with streaming frameworks such a