Lead Data Engineer

Founded in 2016, Innovela is driven by a team passionate about new technologies and their transformative impact on businesses. Leveraging extensive expertise in Cloud technologies and modern digital platforms, we support organizations in accelerating their digital transformation through innovative, scalable, and data-driven solutions.

Based in Paris, we collaborate with international clients to deliver high-impact projects combining Cloud, Data, and AI technologies.

To join a strategic project for a major industrial client based in the United States, we are looking for our future Lead Data Engineer (M/F) .

Your Missions

This is a full-time hybrid role based in Paris, with flexibility for remote work. You will lead the design, implementation, and optimization of modern data platforms and AI-ready architectures in a cloud environment, working closely with engineering, analytics, and business teams.

• Pipelines: Design, develop, and maintain scalable and reliable data pipelines.
• Cloud architecture: Architect modern cloud-based data platforms with a strong focus on Google Cloud Platform (GCP).
• ETL / ELT: Build and optimize ETL / ELT workflows for large-scale industrial datasets.
• Data warehousing: Design and maintain data warehouse and lakehouse architectures.

2. AI & Data Quality (30%)

• Data modeling: Implement data modeling best practices for analytics and AI use cases.
• AI / ML: Contribute to AI and machine learning architecture initiatives.
• Governance: Ensure data quality, governance, security, and performance optimization.
• International: Collaborate with cross-functional and international teams in an English-speaking environment.
• Mentoring: Lead technical discussions and mentor data engineering team members.

Profile Sought

The "Perfect Match" : You're recognized for your expertise in scalable, distributed data architectures, and you know how to turn complex business needs into robust, AI-ready data platforms.

• Expertise: Strong expertise in Data Engineering and scalable distributed data architectures.
• Cloud: Proven experience with Google Cloud Platform (GCP) services, especially BigQuery, Dataflow, Cloud Run, and Pub/Sub.
• ETL / ELT: Strong experience with ETL / ELT frameworks and orchestration tools.
• Data: Solid knowledge of data warehousing, data lakes, and modern analytics architectures.
• Technical: Proficiency in SQL and at least one programming language such as Python.
• International: Experience working in international and industrial environments is a plus.
• Soft skills: Excellent analytical, communication, and leadership skills.
• English: Professional level required (spoken and written).
• Education: Master's degree in Computer Science, Engineering, or a related field.

Nice to have: Experience with AI/ML platforms and MLOps practices, knowledge of Kubernetes and containerized environments, familiarity with Terraform or Infrastructure as Code approaches, experience leading technical teams or large-scale data transformation projects.

• Expertise: Collaborate with experts in cloud, data, and AI technologies.
• Innovation: Contribute to innovative architectures and next-generation platforms.
• Flexibility: Hybrid and flexible working environment.
• Strategic impact: Shape strategic technical decisions in a growing company.

Interview Process

• First conversation (30 min): Mutual introduction with the Recruitment Manager.
• Technical interview (1h): In-depth discussion with a Lead Dev / Architect about your background and skills.
• Meet the team: A coffee or drink with the team to confirm cultural fit!