Product Data Engineer (remote, Europe)

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 like Apache Iceberg

• Have used Pulumi or Terraform for IaC

• Are familiar with Node.js and TypeScript

• Understand AWS cost mechanics (how scale impacts spend)

• Care deeply about code quality and system design

• Are curious about the creator economy (we'll help you get up to speed)

Not a fit if...

• Your data engineering experience is primarily in analytics or BI (dashboards, internal reporting, warehouse modeling for analysts)

• You haven't built and operated data products that ship as part of a customer-facing application

• You're looking for a role focused on stakeholder reporting rather than building production data systems

Benefits

• Fully remote — work from anywhere in Europe

• Unlimited paid vacation 🌴

• Flexible hours — async-friendly culture
  High ownership, low bureaucracy, no bullshit.

• Personal development support — courses, books, or conferences on us

• Regular offsites — connect with your team IRL