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 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

‍ We’re looking for people that

• Are tirelessly in search of the best versions of ourselves – Who want to really show what they’ve got and want to prove the world and themselves what they’re capable of.
• Are direct in their communication – We support and encourage one another through direct, immediate & helpful feedback.
• Know how to become …