Job Opportunities API

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