AI Data Engineer

Growing Pai; Oost-Vlaanderen; Sur place; EUR 70 000 - 100 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Autonomy and ownership

Growth-oriented culture

Practical learning and development

Résumé du poste

Growing Pai in Belgium seeks an AI/Data Engineer to own core data pipelines and vector storage, bridging cloud infrastructure with production AI capabilities.

You will maintain Spark ETL pipelines, optimize SQL views with pgvector and trigram indexing, and deploy AI systems across client environments. The role requires 1+ years deploying AI in production, strong SQL/PostgreSQL skills, and cloud data warehousing experience.

Qualifications

• Proficient in SQL and PostgreSQL.
• Experience with Spark-based ETL pipelines.
• Hands-on with vector search databases (pgvector) and trigram indexing.
• Familiar with deploying AI/ML systems in production.

Responsabilités

• Maintain and scale Spark-based ETL pipelines pulling data from cloud warehouses and load into PostgreSQL.
• Design and optimize SQL views, including vector embedding-backed views.
• Deploy production AI systems and integrate LLMs across client environments.
• Bridge technical architecture and business needs, guiding AI adoption.
• Mentor teammates and promote engineering best practices.

Connaissances

SQL

PostgreSQL

Big Data processing

PySpark

Vector search

LLMs

Cloud platforms

Stakeholder management

Outils

pgvector

trigram search

Description du poste

Join Growing Pai - Where Data Meets Applied AI

At Growing Pai, we deploy and integrate pragmatic AI solutions that transform how businesses analyze data and streamline operations. We don't build AI in a vacuum; we build reliable data foundations and modern AI systems that drive real-world business outcomes.

We are looking for a specialized AI/Data Engineer to take ownership of our core data pipelines and vector storage architecture, bridging the gap between cloud data infrastructure and production AI capabilities.

What You’ll Do

• Maintain & Scale Data Pipelines: Take ownership of existing Spark-based ETL pipelines to extract business data from cloud data warehouses, denormalize it, and efficiently load it into PostgreSQL.
• Optimize Data Models & Vector Stores: Design, tune, and maintain complex SQL views-including vector-embedding-backed views using pgvector and trigram search to expose clean, queryable data for AI applications.
• Deploy Production AI Systems: Implement automated data intake platforms and integrate Large Language Models (LLMs) to enhance operational efficiency across client environments.
• Bridge Tech & Business: Translate business requirements into robust technical architecture, guiding clients and internal stakeholders through seamless AI adoption.
• Drive Continuous Improvement: Stay ahead of modern data and AI stack trends, while mentoring team members and refining engineering best practices.

Who We’re Looking For

• Core Technical Stack: Strong proficiency in SQL, PostgreSQL, and Big Data processing frameworks (e.g., PySpark/Spark ETL).
• AI & Search Infrastructure: Practical experience with vector search databases (pgvector), text search indexing (trigrams), and applying LLMs to business datasets.
• AI Deployment Experience: At least 1+ years of hands‑on experience deploying, integrating, and monitoring AI/ML systems in production environments.
• Cloud & Data Warehousing: Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data warehousing architectures.
• Stakeholder Management: Strong communication skills with a proven track record of translating business needs into data pipelines and functional AI features.

What We Offer

• A competitive salary and benefits package tailored to your experience.
• High impact and autonomy- you will own the backbone of our data and AI infrastructure.
• A supportive, growth-oriented culture focused on practical learning and professional development.
• The chance to build real-world AI systems that drive measurable business outcomes.