Senior Product Data Engineer

🚀 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 specialized 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 (Infrastructure as Code)
• 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:

• Intro chat
• Technical interviews:
  • Coding challenge (in PySpark)
  • System Design
• Team fit / Project presentation
• Culture & alignment call with the CEO Avery Schrader

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 themselves
• Are direct in their communication
• Know how to become autonomous
• Are willing to take ownership to stand up for themselves, their teams, and their communities
• Have fun, are honest, and do great work

Benefits

🎁 What we offer

• Fully remote — work from anywhere in Europe
• Compensation: Annual salary range is 90,000€ - 140,000€ for this role, including stock options
• 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