
A no-code workflow engine that lets teams build, monitor, and maintain production-ready data pipelines for analytics and AI systems.
Added Jun 12, 2026
High opportunity (77%)
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Companies repeatedly need data pipelines that ingest, transform, curate, and merge data across warehouses, vector databases, internal systems, and external sources. These workflows must be reliable, scalable, and clean enough for analytics, business reporting, and AI model consumption, but the job signals show this work still depends heavily on specialized data engineering hires.
Build a SaaS? workflow tool where technical and semi-technical teams can visually define ETL/ELT pipelines, connect common warehouses and data sources, validate data quality, and publish structured datasets for analytics or AI use. The product should include pipeline templates for warehouse ingestion, vector database feeding, data curation, filtering, quality checks, and operational monitoring.
AI and analytics teams increasingly need structured, high-quality datasets from many raw sources, including vector database and model-consumption workflows. The hiring signals show demand across consultancies, product analytics, fraud infrastructure, ML? research, and large-scale device data teams.
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Design and build enterprise-scale data architectures — including data lakes, warehouses, and real-time streaming pipelines. Develop and maintain high-performance ETL/ELT pipelines that process large volumes of structured and unstructured data.
- Design and build automated reports, dashboards, and data pipelines that make recurring analyses self-serve and scalable across EU. - Develop production tools, websites, and ETL pipelines that replace manual processes with reliable, repeatable solutions.
Data Engineering & Modeling: Participate in data acquisition, cleansing, transformation, and mapping to build clean data models for Analytical reporting and AI applications or use cases within SAP and non-SAP ecosystem. Pipeline Development & ETL: Perform data source evaluations, design basic ETL/ELT pipelines, and perform data preparation and business rule development.
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