Job VC
Senior Data Engineer
Technologies
Description
✨ About us
code.store is a French software services company on a mission to enhance business operations by building smart, lean software. We use AI agents, low-code platforms, and SaaS tools to deliver solutions that are fast, efficient, and truly owned by our clients — no technical debt, no long-term dependencies.
We’re both a consulting partner and a delivery powerhouse. That means we don’t just build what clients ask for, we dig deep to understand how they work and how we can help them work better.
🏠 Offices
Our company is headquartered in Paris, yet our tech team operates remotely.
⚡Our Values
Excel at what we do
Provide the best technical and functional quality to our clients
Kindness, honesty, fun, and trust
Stay curious and always keep learning
✏️ Your responsibilities
Own the end-to-end design and implementation of the Modern Data Stack in a highly fragmented and low-maturity environment
Build a production-grade data foundation from scratch, ensuring reliability, scalability, and fast time-to-value
Integrate and reconcile multiple data sources (CRM Batch, Piano, WordPress, analytics tools) into a single source of truth
Design and implement a robust data warehouse architecture aligned with business-critical use cases
Develop, optimize, and orchestrate resilient data pipelines (Airbyte, SQL, orchestration tools)
Define and implement a Master Data Management approach (Golden Record / Master ID) across inconsistent data sources
Take full ownership of data quality, including monitoring, validation, and continuous improvement processes
Translate ambiguous business needs into clear, scalable data models (users, subscribers, interactions, churn signals)
Deliver ready-to-use datasets for churn prediction, segmentation, and CRM activation under tight timelines
Make and defend architecture and tooling decisions, balancing speed vs long-term sustainability
Ensure data is actionable and accessible for data science, product, and business stakeholders
Enable daily operational use cases (e.g., churn scoring, CRM automation) with high reliability
Proactively communicate trade-offs, risks, and limitations to both technical and non-technical stakeholders
🎯 You’re the right candidate if you have
4+ years of hands-on experience in data engineering within Modern Data Stack environments
4+ years of deep experience with advanced SQL and data transformation at scale
4+ years of experience building robust, production-grade data pipelines (ETL/ELT)
Proven experience with data warehouse architecture (BigQuery, Snowflake, Redshift, or equivalent)
Strong understanding of data modeling (analytical & operational) and data system design
Solid experience with data quality frameworks, MDM, and identity resolution in complex environments
Practical understanding of business-driven use cases (churn, engagement, CRM, segmentation)
Ability to work autonomously in low-structure, high-ambiguity environments
Strong ownership mindset with a focus on delivering business impact, not just technical output
English proficiency at B2 level or above
🧩 Will be a big plus
Experience working in subscription-based businesses, digital media, or marketing-driven organizations
Proven track record of building a data platform from scratch under time and resource constraints
Hands-on experience with Airbyte, dbt, and modern orchestration tools
Experience integrating with CRM and product analytics platforms (e.g., Batch, Piano, similar)
Exposure to churn modeling pipelines, feature engineering, and production ML/data science workflows
💻 Tech stack on different projects
Backend: Xano (low-code back-end as a service, database, and API layer), NestJS, Node.js, TypeScript, TRPC
Frontend: Next.js, Custom React frontends (some Content Management Systems provide their own
🤝Hiring process
1h interview with HR and a technical prescreening in English. Please note that your answers will be recorded on video and shared with our tech team for further review
1.5h Technical interview
30 min interview with CTO
code.store is a French software services company on a mission to enhance business operations by building smart, lean software. We use AI agents, low-code platforms, and SaaS tools to deliver solutions that are fast, efficient, and truly owned by our clients — no technical debt, no long-term dependencies.
We’re both a consulting partner and a delivery powerhouse. That means we don’t just build what clients ask for, we dig deep to understand how they work and how we can help them work better.
🏠 Offices
Our company is headquartered in Paris, yet our tech team operates remotely.
⚡Our Values
Excel at what we do
Provide the best technical and functional quality to our clients
Kindness, honesty, fun, and trust
Stay curious and always keep learning
✏️ Your responsibilities
Own the end-to-end design and implementation of the Modern Data Stack in a highly fragmented and low-maturity environment
Build a production-grade data foundation from scratch, ensuring reliability, scalability, and fast time-to-value
Integrate and reconcile multiple data sources (CRM Batch, Piano, WordPress, analytics tools) into a single source of truth
Design and implement a robust data warehouse architecture aligned with business-critical use cases
Develop, optimize, and orchestrate resilient data pipelines (Airbyte, SQL, orchestration tools)
Define and implement a Master Data Management approach (Golden Record / Master ID) across inconsistent data sources
Take full ownership of data quality, including monitoring, validation, and continuous improvement processes
Translate ambiguous business needs into clear, scalable data models (users, subscribers, interactions, churn signals)
Deliver ready-to-use datasets for churn prediction, segmentation, and CRM activation under tight timelines
Make and defend architecture and tooling decisions, balancing speed vs long-term sustainability
Ensure data is actionable and accessible for data science, product, and business stakeholders
Enable daily operational use cases (e.g., churn scoring, CRM automation) with high reliability
Proactively communicate trade-offs, risks, and limitations to both technical and non-technical stakeholders
🎯 You’re the right candidate if you have
4+ years of hands-on experience in data engineering within Modern Data Stack environments
4+ years of deep experience with advanced SQL and data transformation at scale
4+ years of experience building robust, production-grade data pipelines (ETL/ELT)
Proven experience with data warehouse architecture (BigQuery, Snowflake, Redshift, or equivalent)
Strong understanding of data modeling (analytical & operational) and data system design
Solid experience with data quality frameworks, MDM, and identity resolution in complex environments
Practical understanding of business-driven use cases (churn, engagement, CRM, segmentation)
Ability to work autonomously in low-structure, high-ambiguity environments
Strong ownership mindset with a focus on delivering business impact, not just technical output
English proficiency at B2 level or above
🧩 Will be a big plus
Experience working in subscription-based businesses, digital media, or marketing-driven organizations
Proven track record of building a data platform from scratch under time and resource constraints
Hands-on experience with Airbyte, dbt, and modern orchestration tools
Experience integrating with CRM and product analytics platforms (e.g., Batch, Piano, similar)
Exposure to churn modeling pipelines, feature engineering, and production ML/data science workflows
💻 Tech stack on different projects
Backend: Xano (low-code back-end as a service, database, and API layer), NestJS, Node.js, TypeScript, TRPC
Frontend: Next.js, Custom React frontends (some Content Management Systems provide their own
🤝Hiring process
1h interview with HR and a technical prescreening in English. Please note that your answers will be recorded on video and shared with our tech team for further review
1.5h Technical interview
30 min interview with CTO