Senior Product Data Engineer (remote, Europe)

Remote — Data Insights Team — Full-time Modash 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.⁠⁠⁠​ 🚀 What your day-to-day will look like We’re not a service function — Data Search & Data Insights are core product capabilities at Modash, building products for customers to use. 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 standup - Heads-down focus time to plan, build, iterate, and launch - Minimal meetings — maximum ownership You’ll be working on big, impactful projects like: - Creating an understanding of the creators location, age, and interests at scale - Creating systems to extract collaborations between creators and brands from raw social data - Shaping 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. 👥 The Data Team 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 compute - GCP Vertex Batch API for LLMs - Airflow for orchestration - Iceberg and Aurora (Postgres) for persistence - Other: S3, Glue, Kinesis, Lambda, ECS, Athena - Tools: Slack, GitHub, Linear, Notion, Cursor 🧪 The interview process We move fast. You can get interviewed in under a week. Process consists of: 1. Intro chat 2. Technical interviews: 1. Coding challenge (in PySpark) and 2. System Design 3. Team fit / Project presentation 4. Culture & alignment call with the CEO Avery Schrader - That’s it! Requirements 🛠 Skillset we’re looking for - Strong knowledge of Spark (Scala, Databricks, or PySpark; PySpark preferred but not required) - Proven track record with ETL/ELT pipelines and large-scale data processing - Comfortable working with unstructured data - Experience with workflow orchestration tools like Airflow or AWS Step Functions - Familiarity with the AWS ecosystem (Glue, EMR, etc.) - You've shipped full features from idea to production: planning & scoping → architecture → implementation → release → iteration - Based in Europe with significant working-hours overlap with EET (Tallinn time) - Hands-on experience building agentic / LLM-powered features in production - Practical understanding of trade-offs between LLMs (cost, latency, capability) ✅ Bonus points if you… - Have worked with AI/ML tools or LLMs - Are familiar with the GCP stack (especially Vertex AI) - Have worked with lakehouse formats