Junior Data & Automation Engineer

Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive platform, with AI agents that work alongside every team, from Finance to HR, to build, adapt, and align strategic plans in real time.
Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally, passing $100M in ARR in 2026 and doubling revenue for the second year in a row. Industry leaders like Unilever, Uber, Anthropic, Snowflake, and Siemens use Pigment every day to make better-informed decisions and navigate any scenario with confidence.
In October 2026, we raised a $250M Series E at a $2.3B valuation, bringing our total funding to $650M+. Today we’re a growing team of 700+ across Paris, London, New York, Toronto, San Francisco, and Austin, and we’ve been named a Visionary in the Gartner® Magic Quadrant™ for Financial Planning Software two years running.
At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo - all while working as one team. If you’re driven by innovation and ready to make an impact at scale, we’d love to hear from you.

The Data & Automations Team

The Data & Automations team builds and operates Pigment's internal data platform, and designs, implements, and maintains the intelligent automation solutions that rely on it. Together, they streamline business processes and enhance data-driven decision making: we empower product, business and corporate functions through technology integration, robust data architecture, and process optimization, enabling teams to focus on high-value activities while ensuring accuracy and scalability.

The data platform is the foundation of everything we deliver. It is a centralized, governed ecosystem that collects, stores, transforms, and serves data to internal consumers across Product, Go-To-Market (GTM), and General & Administrative (G&A) functions, providing a single source of truth for analytics, automations, and AI. Making it reliable, secure, cost-efficient, and scalable is at the core of our mission. The team also consolidates and orchestrates AI efforts across Pigment, from governance and enablement to building AI-powered solutions.

Our team tackles diverse challenges, from integrating finance and HR systems and streamlining employee lifecycle processes, to building pipelines that turn product usage and customer interactions into actionable insights for Finance or GTM teams. AI is now at the center of most of what we do with data: many of our pipelines feed LLM-powered solutions, and the quality, structure, and governance of our data architecture directly determine what these solutions can deliver.

The team is led by Pigment's Deputy CISO and works closely with the Security team: security and data governance are part of how we build, not an afterthought.

Role

As a Junior Data and Automations Engineer, you will contribute to the continued development of Pigment's data platform: ingestion pipelines, dbt models, orchestration, data quality, and the underlying cloud infrastructure. You will also build and maintain the data pipelines, automations, and AI projects that support our G&A (Finance, People, IT) and GTM (Sales, Customer Success, Partnerships) teams.

You will work closely with senior engineers, starting with well-scoped tasks and progressively taking ownership of small projects end to end, from requirements gathering to production monitoring. This role involves collaborating with a wide range of internal stakeholders and requires excellent communication skills in English (primarily) and French, verbal and written.

Tech environment

Our core stack relies on Google Cloud Platform, maintained with Terraform, with components including BigQuery, Cloud Run, and Cloud Composer (Airflow), as well as dbt, Fivetran, Hightouch, Elementary for data observability, and Python for integrations and automations. Our pipelines connect business systems such as Salesforce, NetSuite, our HRIS, Gong, or Slack, and feed Pigment applications used by our own business teams. We also build LLM-powered pipelines and use AI tools in our daily engineering work.

You will have the opportunity to learn and grow your skills across these technologies while making a meaningful impact on Pigment's operational efficiency.

Key Responsibilities

Under the supervision of the Data & Automations team's more senior members, you will participate in addressing the following topics.

Data Platform & Infrastructure:

• Develop and maintain ingestion pipelines from APIs, databases, and SaaS tools, using Fivetran, Airflow, and Python
• Build and maintain dbt models that turn raw data into clean, documented, and tested datasets
• Contribute to the evolution of our orchestration, CI/CD, and infrastructure-as-code setup
• Help improve data quality, observability, and alerting across the platform

G&A and GTM Data Pipelines & Automations:

• Build pipelines and integrations that sync data between business systems (CRM, ERP, HRIS) through our data warehouse, including reverse ETL with Hightouch
• Develop Python-based automations that remove manual work for teams such as Finance, People, IT, and Customer Success
• Prepare reliable datasets for reporting and for the Pigment applications used by business teams

AI Projects:

• Contribute to AI-powered solutions, such as LLM pipelines that extract, classify, and enrich unstructured data (call transcripts, messages, tickets)
• Build the data foundations these projects rely on: AI-ready datasets, usage and observability data, evaluation data
• Apply data architecture principles that make our data reliable, well-documented, and safely accessible for AI use cases (context, retrieval, access scoping)

Monitoring & Support:

• Monitor pipelines and automations, troubleshoot incidents, and fix root causes
• Document data models, pipelines, and processes for both technical and business readers

Collaboration & Learning:

• Work with stakeholders - as diverse as Finance, People, Sales, and Product - to understand requirements and translate them into data solutions
• Participate in code reviews and knowledge sharing sessions
• Continuously expand your knowledge of data engineering, automation, and AI best practices