Senior Product Data EngineerModash gives brands the tools to work with the right content creators and helps creators earn a living doing what they love. Behind the scenes, the Data Insights team is building the intelligence layer that turns raw social media signals into trusted, customer-facing data products — with reliable access, quality, and freshness at scale.We're looking for a hardened Senior Product Data Engineer to help us scale these systems end-to-end, raise our quality bar, and accelerate how quickly we turn messy public data into consistent, valuable insights customers can build on.Data Insights is a specialised team in Data Org, and you'll own high impact projects end-to-end, from idea to launch.Here's a typical day:Start your day with a short standupHeads-down focus time to plan, build, iterate, and launchMinimal meetings — maximum ownershipYou'll be working on big, impactful projects like:Creating an understanding of the creators location, age, and interests at scaleCreating systems to extract collaborations between creators and brands from raw social dataShaping the future of AI-assisted search, exploring how LLMs and embeddings can enhance search and recommendations.You won't be patching pipelines — you'll be creating data products from scratch that directly impact customers.At Modash, the Data Insights team isn't a support function — it's a core part of the product. You'll join a growing group of data and backend engineers, working within our broader Data organization.We work in three closely aligned teams within Data:Data Insights — builds the creator and brand-level insight products and APIs (e.g., collaborations, reports, dictionaries, contacts, audience overlap).Data Search — owns our search products (including AI Search) end-to-end.Data Core — responsible for raw data collection and the foundations of our data platform.We value autonomy, but we also work closely as a team — through pair programming, fast feedback loops, and shared wins.
Everyone is expected to take ownership, but nobody works in isolation.We're remote-first, and we also make time to connect IRL through regular team offsites — to have fun, collaborate, and reflect.Our tech stack:AWS and GCP with Pulumi (IaC)PySpark on AWS EMR for computeGCP Vertex Batch API for LLMsAirflow for orchestrationIceberg and Aurora (Postgres) for persistenceOther: S3, Glue, Kinesis, Lambda, ECS, AthenaTools: Slack, GitHub, Linear, Notion, CursorThe interview process:Intro chatTechnical interviews: 1. Coding challenge (in PySpark) and 2. System DesignTeam fit / Project presentationCulture & alignment call with the CEO Avery Schrader - That's it!