Founding Data Engineer

Botpress, Inc.; Montreal; On-site; CAD 80,000 - 120,000; Full time

Job summary

A tech company focused on AI is seeking a founding Data Engineer to establish their data platform. The role involves building data pipelines, collaborating with different teams for data insights, and mentoring future hires. This position offers an excellent opportunity to influence revenue and customer growth directly.

Benefits

Mentorship opportunities

Direct influence on company growth

Chance to shape the data platform

Qualifications

• 3+ years building data infrastructure at early-stage startups.
• Solid understanding of event tracking best practices.
• Experience with reverse-ETL and BI & Product Analytics tools.

Responsibilities

• Design, build, and maintain ingestion pipelines to BigQuery.
• Define and document event schema and collaborate on analytics.
• Build dashboards tracking campaign performance and funnel conversion.

Skills

Data pipelines

Event tracking

Communication

Hands-on experience with BigQuery

Proficiency in dbt

Production-grade Python or SQL

Reverse-ETL

Data-quality frameworks

Education

Bachelor's degree in a related field

Tools

BigQuery

Hightouch

Segment

Looker

Metabase

Superset

Mixpanel

Job description

About Botpress

At Botpress, our platform empowers organizations to integrate AI agents into their core business functions. We are dedicated to becoming the standard solution for multi-agent systems, serving enterprises, governments, and educational institutions of various scales.

We keep our team intentionally small & talent-dense and are looking for highly skilled and motivated people who bring something exceptional to our group.

Role Overview

As a Series A, product-led growth company, we’ve built an early data stack and now need our first Data Engineer to dedicate themselves solely to building and owning our data platform. This person will live at the intersection of data infrastructure and go-to-market, partnering deeply with our Sales, Marketing, and Engineering teams to drive fast, reliable insights that fuel growth.

Key Responsibilities

End-to-End Data Platform Architecture

• Design, build, and maintain ingestion pipelines from Segment & HubSpot into BigQuery.
• Use dbt to transform raw tables into curated models (e.g., Active Users, PQLs, MRR dashboards).
  

Instrumentation & Event Schema

• Define and document event schema in a shared spec (e.g., Git-backed Markdown).
• Collaborate via PRs: draft the spec, review front-end analytics.track() implementations, and own CI smoke tests to validate payloads.
  

Reverse-ETL & Data Activation

• Implement and manage tools like Hightouch or Segment to push enriched segments (e.g., PQLs) back into HubSpot for Sales workflows.
• Automate lead scoring, account segmentation, and churn prediction signals.
  

Self-Serve GTM Analytics

• Build and maintain dashboards in Looker/Metabase/Superset that track funnel conversion, campaign performance, and product usage trends.
• Partner with GTM stakeholders to triage ad-hoc analyses, produce weekly reports, and enable data-driven decision-making.
  

Experimentation Infrastructure

• Stand up basic A/B test pipelines (data capture, analysis templates) to optimize onboarding flows and marketing campaigns.

• 3+ years building data infrastructure at early-stage startups or high-velocity teams.
• Solid understanding of event tracking best practices: event schema design, payload validation, instrumentation reviews.
• Excellent communication: you can write clear event specs, document data models, and lead cross-functional working sessions.
• Hands-on experience with BigQuery (or similar DW)
• Proficiency in dbt (or equivalent ELT framework) and production-grade Python or SQL.
• Experience with reverse-ETL (Hightouch, Segment).
• Familiarity with data-quality frameworks and BI & Product Analytics tools (Looker, Metabase, Mixpanel).
• Familiarity with marketing automation principles and CRM workflows in a PLG environment is a plus.

Who You Are

• Generalist mindset: You’ve built data pipelines and also dipped your toes in product instrumentation, reverse-ETL, and BI.
• Code-first: Comfortable authoring and reviewing PRs, writing Python/SQL for ETL, and collaborating with software engineers.
• Business-obsessed: Understands how data infrastructure supports business results and data science work. Designs pipelines and integrations with end users in mind (e.g., model training, reporting), proactively monitors data quality, and takes ownership of keeping critical datasets reliable and usable.
• Autonomous yet collaborative: You love owning big initiatives end-to-end but know how to partner tightly with GTM, Product, and Engineering leads.
• Infrastructure-minded: You care about scalability, drift-detection, and minimizing technical debt from day one.
• Outcome driven: You solve complex problems creatively, always prioritizing key outcomes.

Why You’ll Love Working Here

As our founding Data Engineer hire, you will:

• Shape the foundation of our data platform and be the go-to expert for all things data.
• Be the bridge between our product data and our go-to-market efforts, directly influencing revenue and customer growth.
• Mentor future hires (data analysts, data engineers) and establish best practices for data at scale.

If you’re passionate about building data-driven systems that power real-time insights and customer-centric automation, we’d love to hear from you.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, marital status, veteran status, or disability status.