Senior Data Engineer

Do you want to work on a Data Platform that serves an entire fintech scale-up — from Marketing to Product, Finance, Customer Success, and Sales — and that is currently at the heart of our AI-first transition? Do you have the perspective to maintain production systems AND the energy to build the semantic layer that will connect our data to AI?

At Agicap, the Data Platform meets analytics (reporting, AI) and data synchronization needs for the entire company. It relies on Google Cloud Platform (especially BigQuery and Composer), Airbyte, dbt, and Looker to maintain and distribute up-to-date, consolidated, and reliable data.
🔥 The game-changing project: opening up access to company data through AI via our MCP Analytics server. We have already laid the groundwork with Looker Explores governed by Data Analysts — the logical next step is extending this to BigQuery coupled with a semantic layer. And that's where you come in.

You will alternate between demanding operational maintenance and structuring projects:

• Maintain and ensure the reliability of the platform: Composer (Airflow), Airbyte self-hosted on GKE, BigQuery, dbt, Terraform. A portion of your time will be dedicated to operations (incident management, Data Analyst support), shared within the DE team. You will design and enhance tests, monitoring, and alerting — both technical and functional.
• Industrialize data ingestion: collect sources via Airbyte (API or CDC as appropriate), manage schema evolution, and BigQuery external tables.
• Feed business tools: reverse-ETL and synchronizations between tools (HubSpot, Gainsight, Intercom…) or to our real-time PostgreSQL database via our streaming architecture (webhooks → Pub/Sub → Cloud Run).
• Extend the AI access layer: extend MCP Analytics to BigQuery, build the semantic layer that conditions the quality of AI responses. The quality of the modeling determines the quality of the responses.
• Control costs and security: BigQuery slot reservations with autoscaling, dynamic dbt build routing, monthly FinOps review, least privilege, management of personal and sensitive data, securing AI data access.

• GCP: BigQuery, GCS, Pub/Sub, Cloud Run, Cloud SQL, Composer, GKE, Looker
• Ingestion: Airbyte self-hosted (CDC PostgreSQL and SQL Server), GCS Avro → BigQuery external tables
• Transformation & Quality: dbt, Elementary
• IaC & CI/CD: Terraform, Cloud Build, GitHub Actions
• Languages: Python, SQL, Docker
• AI: Claude Code (internal skills and plugins), internal MCP server

Essential

• Minimum 5 years of experience in Data Engineering on a major Cloud Provider, with responsibility for maintaining systems in production.
• Proficient SQL + complex dbt models (incremental materialization, snapshots, macros) that you know how to debug (duplicates, late data, deletions, schema changes) and optimize (duration, cost).
• Solid experience in pipeline ingestion and orchestration: debugging, schema drift, recovery, backfilling, impact analysis.
• High-quality Python, tested and mastered — maintainability and reliability at the core of your practice.
• Infrastructure as Code and CI/CD on a daily basis.
• You work with a Coding Agent and know how to take a step back to verify its output.
• You are proactive, rigorous, humble, and you enjoy sharing knowledge: sharing your discoveries, explaining your choices to both technical and business teams, helping your colleagues progress.
• You are comfortable working in a partially full-remote team.
• Minimum B2 English.

A significant plus

• Experience with a semantic layer (dbt Semantic Layer / MetricFlow, LookML), on GCP Knowledge Catalog (formerly Dataplex) or equivalent, or more broadly in data governance: cataloging, lineage, classification, policy tags, ownership.
• Processing in event-driven architecture and its specificities (Pub/Sub, Cloud Run, scaling, retries, dead-letter queues).

A plus

• GCP experience: BigQuery and its compute model via slot reservations, Composer, Cloud Run, GKE / Helm.
• You have built tools for AI agents (MCP server, skills).
• Integrations into business tools (HubSpot, Gainsight, Intercom).
• Data pipelines using Change Data Capture.
• Contributions to the Airbyte ecosystem.

1. Screening with our Senior Talent Acquisition — 45 min on your background and motivation.
2. 1st technical interview with Pauline (Head of Data) — technical discussion, challenge on problem-solving approaches, topic framing, Agicap use case — 1h.
3. 2nd technical interview with Kévin (Team Lead DE) and Julien — SQL test + oral architecture test + technical discussion + AI case — 2h.