Senior Enterprise Data Platform Engineer - AI-Ready Pipelines

Jedox; United States; Remote; USD 130,000 - 190,000; Full time

Job summary

Jedox is seeking a Senior Data Engineer in the United States to own and design our enterprise data platform, building a scalable Fabric-based lakehouse and robust data pipelines. You will integrate diverse data sources, ensure data quality, and enable AI-ready datasets for enterprise applications.

You'll collaborate across AI, analytics, and business teams, implementing semantic models, metadata governance, and secure data access.

Qualifications

• 7+ years in data engineering experience.
• Expertise in Python and SQL.
• Experience with Spark and Microsoft Fabric.
• Hands-on Delta Lake, Azure Data Platform, ETL/ELT.
• Experience integrating enterprise systems (Salesforce, SharePoint, M365, Azure SQL/Data Lake).
• Knowledge of metadata management and semantic modeling.
• Azure/Fabric certifications and experience with Purview, Synapse, Data Mesh or similar.

Responsibilities

• Design and own the enterprise data platform with a scalable Microsoft Fabric data lakehouse (Bronze/Silver/Gold).
• Develop and operate batch and streaming ETL/ELT pipelines with schema evolution and data quality checks.
• Integrate sources like SharePoint, Salesforce, M365, Azure SQL, ERP/CRM systems, and REST APIs.
• Optimize storage and processing for both structured and unstructured data with monitoring and reliability.
• Build semantic data layers, data cataloging, lineage tracking, and access controls.
• Prepare data for AI use cases including embedding pipelines and RAG readiness.
• Expose reusable APIs and data services; collaborate with AI, analytics, and business teams.

Skills

Python

SQL

Spark

AI/ML data prep

Data modeling

Tools

Microsoft Fabric

Delta Lake

Azure Data Platform

REST APIs

Job description

Jedox is seeking a Senior Data Engineer in the United States to own and design our enterprise data platform, building a scalable Fabric-based lakehouse and robust data pipelines. You will integrate diverse data sources, ensure data quality, and enable AI-ready datasets for enterprise applications.

You'll collaborate across AI, analytics, and business teams, implementing semantic models, metadata governance, and secure data access.