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Pigment

SaaS platform for advanced financial reporting

Junior Data & Automation Engineer

Data EngineeringPosted on Nov 9
Full-timeParis, France

About the Job

Requirements

  • Up to 3 years of relevant experience in data engineering, including apprenticeships, internships, and/or demonstrable personal projects.
  • Strong SQL skills and understanding of data modeling concepts, such as layered or dimensional models.
  • Solid coding skills in Python.
  • Understanding of ELT/ETL patterns, pipeline design, and data quality testing.
  • Knowledge of version control systems such as Git and CI/CD concepts.
  • Practical experience with a public cloud provider and a cloud data warehouse.
  • Ability to identify edge cases through attention to detail and analytical problem-solving.
  • Good understanding of artificial intelligence and large language model principles, along with practical use of artificial intelligence tools in work.
  • Excellent written and verbal communication skills in French and English.

Responsibilities

  • 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 orchestration, CI/CD, and infrastructure-as-code setup.
  • Help improve data quality, observability, and alerting across the platform.
  • Build pipelines and integrations that sync data between business systems, including CRM, ERP, and HRIS, through the data warehouse, including reverse ETL with Hightouch.
  • Develop Python-based automations that remove manual work for Finance, People, IT, and Customer Success teams.
  • Prepare reliable datasets for reporting and for Pigment applications used by business teams.
  • Contribute to artificial-intelligence-powered solutions, such as large language model pipelines that extract, classify, and enrich unstructured data including call transcripts, messages, and tickets.
  • Build the data foundations for artificial intelligence projects, including AI-ready datasets, usage and observability data, and evaluation data.
  • Apply data architecture principles that make data reliable, well-documented, and safely accessible for AI use cases, including context, retrieval, and access scoping.
  • Monitor pipelines and automations, troubleshoot incidents, and fix root causes.
  • Document data models, pipelines, and processes for technical and business readers.
  • Work with stakeholders across Finance, People, Sales, and Product to understand requirements and translate them into data solutions.
  • Participate in code reviews and knowledge-sharing sessions.
  • Develop and maintain Python-based automations and solutions to streamline enterprise processes.
  • Implement integrations between systems and applications using APIs and other connection methods.
  • Assist in maintaining CI/CD pipelines for automation projects.
  • Support implementation of data pipelines that integrate data from APIs, external databases, and third-party services.
  • Assist in transforming raw data into clean, ready-to-use models using SQL and dbt.
  • Collaborate on data quality monitoring and improvement initiatives.
  • Help implement monitoring for automation workflows and data pipelines.
  • Troubleshoot and resolve issues with existing automation solutions.
  • Assist with documenting systems, processes, and workflows.
  • Work with team members and stakeholders across HR, Sales, and Product Engineering to understand requirements and implement effective solutions.
  • Continuously expand knowledge of data engineering, automation, and AI best practices.

Desired Qualifications

  • Hands-on experience with dbt, Airflow, or Terraform.
  • Exposure to ingestion and reverse ETL tools.
  • Hands-on experience building large language model-powered pipelines or applications.
  • Basic project management capabilities, including tracking tasks, managing timelines, and reporting progress.
  • Hands-on experience through personal projects, particularly contributions to open-source initiatives, is valued equally to professional and academic experience.

About the Company

Pigment

SaaS platform for advanced financial reporting

Pigment provides a SaaS FP&A platform that helps businesses create and manage advanced financial reports and forecasts. It connects data, performs large calculations, and enables team collaboration to build detailed models (HR, revenue, operating expenses, and cash flow) beyond traditional spreadsheets. It differentiates itself with a user-friendly design, strong processing power, and easy connectivity that support granular, scalable financial scenarios. Its goal is to make financial reporting and forecasting faster, more accurate, and accessible so teams save time and focus on analysis and value creation.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$646.9M
Headquarters
Paris, France
Founded
2019

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