Data Engineer

• Contribute to the design and build of a modern, scalable data platform from greenfield — participate in decisions on cloud infrastructure, data ingestion, transformation, storage, and serving layers
• Apply and help refine data modeling standards, pipeline patterns, ingestion frameworks, and governance practices
• Help ensure the platform meets HIPAA and GDPR compliance requirements and incorporate those constraints into your work
• Support the full project lifecycle for platform initiatives: help define scope, track timelines, manage dependencies, and deliver with a bias for action
• Proactively identify gaps and risks in the data landscape — bring problems to the table with proposed solutions
• Drive tasks end-to-end: take ownership, manage your own blockers, and follow through
• Partner with the broader data engineering function and contribute as a collaborative technical voice on platform direction
• Translate business and clinical data needs into technical implementation, balancing pragmatism with long-term scalability
• Collaborate with stakeholders across Sweden, the UK, the US, and local markets — strong asynchronous communication and comfort operating across time zones required
• Establish and optimize data models and architectures (e.g., lakehouse, data warehouse, data mesh) to support enterprise-wide data accessibility and performance
• Proactively identify gaps, risks, and opportunities in the data landscape — present problems with solutions, not just observations
• Comply with company and departmental policies and administrative requirements
• Perform other duties as assigned or needed

Data Engineer – Data Platform

• Vous servirez de passerelle entre une architecture technique complexe et la valeur commerciale stratégique.
• Vous serez la principale autorité technique pour nos clients.
• Agir en tant que partenaire stratégique principal auprès des responsables métiers clients.
• Piloter le développement d'architectures de données complexes et à grande échelle.
• Superviser les performances de livraison de plusieurs équipes.
• Diriger le tri et la résolution des incidents critiques de la plateforme.
• Mettre en œuvre des cadres de gouvernance robustes et des contrôles de conformité.
• Promouvoir une culture organisationnelle de partage des connaissances.
• Influencer la santé à long terme de l'organisation.

Principal Data Engineer – Contractuel

• Delivery / Conseil & Expertise: Conception et mise en œuvre d'architectures Data modernes (Cloud & On-premise)
• Réalisation d’audits, définition de roadmaps, accompagnement sur les choix technologiques
• Réalisation de PoC/MVP, coaching technique, conduite du changement
• Participation à l’écosystème tech (Meetups, afterworks, partenaires, éditeurs…)
• Contribution active à notre communauté d’experts Data (Snowflake, AWS, GCP, Azure, Databricks, DBT, Looker, Rivery, Airbyte, etc.)
• Accompagnement des équipes commerciales sur les réponses techniques
• Participation à la formalisation des offres et des convictions Data de l’agence
• Accompagnement de consultants en mission, animation de la communauté, recrutement, entretiens techniques

Data Architect

• Conceive, develop and industrialize reliable and high-performance data pipelines
• Integrate structured and unstructured data, both in batch and real-time
• Deploy and optimize data environments on the Cloud (AWS, Azure, GCP)
• Implement and orchestrate ETL/ELT processes (Talend, Airflow, dbt, Fivetran, etc.)
• Work on modern environments such as Databricks, Snowflake, BigQuery, Redshift
• Ensure data quality, security and governance
• Contribute to technology watch and recommend the best solutions for each project

• Build a clear understanding of Vibe’s key data flows, sources of truth, and ownership.
• Help define schemas, data contracts, documentation, and standards for how data should be used across the company.
• Improve data discoverability so teams can confidently understand what data exists, where it lives, and how to use it.
• Establish practical standards around data quality, lineage, observability, and ownership.
• Define, maintain and enforce data lifecycle policies.
• Help teams track data cost and usage.
• Define and implement data compliance practices aligned with Vibe’s business, partners, and regulatory needs.
• Partner with Legal, Product, Security, and Engineering to assess the impact of new data sources, partnerships, and use cases.
• Help clarify what data can be used, how it can be used, where it should live, and how long it should be retained.
• Support Vibe’s ability to work confidently with premium publishers, enterprise advertisers, and strategic partners.
• Build guardrails, not gatekeepers, enabling engineers and teams to move fast while making safe, compliant decisions.
• Embed governance and compliance into existing engineering workflows, tools, and architectural decisions.
• Help Vibe transition toward a more security, and compliance-aware, data culture.
• Identify the biggest risks, gaps, and opportunities, then define a pragmatic roadmap to address them.

Principal Data Engineer – Governance & Compliance

• Design and develop data ingestion, processing, and modeling pipelines using DBT
• Optimize SQL queries on BigQuery to ensure data performance and reliability
• Model the semantic layer with Looker/LookML to enable business users to leverage the data
• Automate workflows using GitLab CI/CD and Docker Compose
• Collaborate in an Agile (Scrum) environment with technical and business teams to deliver high-value data solutions

Data Engineer, DBT, SQL

• Integrated within Nathalie’s team (Application IT Manager)
• Transform raw data into reliable, actionable information
• Work on data architecture and pipelines
• Contribute to the design, deployment and operation of the company’s data platform
• Participate in designing the data architecture
• Help select technologies and tools (ETL/ELT, storage, orchestration)
• Define data models tailored to analytical needs
• Design and maintain data ingestion and transformation pipelines
• Automate data flows from various sources
• Optimize pipeline and query performance
• Supervise and monitor data pipelines
• Ensure data quality, reliability and consistency
• Assist in implementing a BI tool
• Facilitate workshops to gather and analyze business requirements
• Collaborate with business teams to define key performance indicators (KPIs)

• Concevoir, développer et maintenir les pipelines d'ingestion et de transformation des données
• Contribuer à la modélisation médaillon (Bronze / Silver / Gold) sur BigQuery
• Développer et faire évoluer les modèles dbt (tests, documentation, lineage)
• Orchestrer les traitements via Cloud Composer (Airflow) et Dataproc (Spark)
• Garantir la qualité, la fiabilité et la performance des traitements en production
• Collaborer avec les Data Analysts pour exposer les bonnes données aux bons utilisateurs

Data Engineer, GCP

• support the ML engineers by improving our MLOps platform
• Work closely with software engineers to implement the data science algorithms in the client applications in a safe, scalable and maintainable way
• Exchange with the platform team to keep the infrastructure debt at a minimum
• Help the team deploy our algorithms in production in a safe, scalable and maintainable way

Data Engineer – Internship

• Take end-to-end ownership of highly visible projects from initial ideation to production release.
• Actively partner across the entire data lifecycle to discover high-impact feature opportunities.
• Collaborate closely with Data Scientists and ML Engineers to design, scale, and optimize core components.
• Build, maintain, and optimize mission-critical data pipelines spanning both extensive batch processing and continuous real-time streams.
• Actively build and maintain the high-load backend applications that power our ML model serving.
• Work hand-in-hand with our infrastructure teams to guarantee the reliability, security, and immense scalability required for an ad-network ecosystem.
• Thrive in a fast-paced agile environment with rapid decision-making processes.
• Actively contribute to our engineering culture, share knowledge, and ensure every team member feels comfortable, supported, and empowered to grow in their role.

Senior Data Engineer – Feature Platform

• You will join our Data Engineering team based in Paris and in charge of building our Addressability features.
• You will be onboarded in a multi expertise feature team of back-end developers and Data Engineers, with the mission to build and query a multi billion entry Id Graph, plug third party data providers and provide business teams with in depth behavioural analytics.
• Integration of external partners into the graph
• Evaluation of our graph vs. partners' graphs
• Monitoring + failsafe to produce a stable graph
• Improvement of our graph by taking more parameters into account
• Design trade offs (feature vs performance)
• Business support on external partners' coverage analyses
• Integration of retail media IDs into the graph for simplified attribution

Freelance Data Engineer, Addressability

• Design, build, and maintain ingestion/processing pipelines at scale using Python/SQL and Spark; operate within a lakehouse stack (Apache Iceberg or Delta Lake).
• Implement and optimize workflows on Databricks (Jobs, Workflows, Delta) and/or Snowflake (Warehouses, Tasks, Streams) and/or native cloud provider solutions (AWS / AZURE).
• Improve performance, reliability, and cost on AWS (S3, Redshift, Athena/Glue, Lambda), with strong observability and IaC practices.
• Apply security-by-design, data governance, and compliance best practices across storage, compute, and sharing layers.
• Partner with Product team and R&D team to prepare data for initial AI/ML use cases (feature pipelines, data quality, lineage).
• Enable secure, efficient data access for customers via connectors, APIs, and lakehouse sharing patterns (e.g., Delta Sharing, Snowflake data sharing).

• Design and industrialize data ingestion, transformation, and exposure pipelines on Google Cloud Platform (Dataflow, Cloud Functions, Pub/Sub, Cloud Composer)
• Model and manage a BigQuery data warehouse following a layered architecture (Data Warehouse / Data Mart) optimized for large-scale analytics
• Write and optimize complex SQL queries (window functions, partitioning, clustering, scan cost optimization)
• Implement data quality controls: consistency tests, anomaly detection, alerting
• Deploy and version data infrastructure using Terraform (BigQuery, GCS, IAM, service accounts, scheduled queries…)
• Set up CI/CD workflows to ensure reproducibility and traceability of deployments
• Document Terraform modules and maintain a resource catalog
• Build and maintain Looker Studio dashboards connected to BigQuery
• Ensure report performance (query optimization, caching, extracts)
• Maintain consistency of metrics across different dashboards
• Contribute to defining Data standards (naming conventions, SQL code review, documentation)
• Stay up to date on the GCP ecosystem and propose improvements
• Mentor junior profiles on Data Engineering best practices

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