Senior Product Data Engineer (remote, Europe)
Modash • Vilnius, Vilnius City Municipality, Lithuania • Cluj-Napoca, Cluj County, Romania
Posted: May 15, 2026
Job Description
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!
Remote — Data Insights Team — Full-timeModash 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 ...🛠 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 autonomous - Who we can trust to do their best work without needing processes to guardrail.
- Are willing to take ownership to stand up for ourselves, our teams, and our communities.
- Have fun, are honest, and do great work – No title chasers, no finger pointers, no being awful. Absolutely no slowing down to protect ego.
Additional Content
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!
Remote — Data Insights Team — Full-timeModash 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 ...🛠 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 autonomous - Who we can trust to do their best work without needing processes to guardrail.
- Are willing to take ownership to stand up for ourselves, our teams, and our communities.
- Have fun, are honest, and do great work – No title chasers, no finger pointers, no being awful. Absolutely no slowing down to protect ego.