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

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Other: S3, Glue, Kinesis, Lambda, ECS, Athena

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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