Data Engineering Lead

Responsibilities

• Lead the design and development of end-to-end data architecture and canonical data models for an Intelligent Invoice-to-Cash platform
• Build and maintain scalable batch and real-time data pipelines ingesting data from ERP, banking, and EDI systems
• Design data pipelines that power AI-driven document processing, matching, and reconciliation models
• Implement data validation, reconciliation, and monitoring frameworks to ensure financial data accuracy and security
• Lead a team of data engineers and partner with AI, Integration, and Product teams to drive the data roadmap
• Enable KPI dashboards and optimize data availability for near real-time reporting and analytics

Requirements

• 8–14+ years of experience in data engineering or data architecture
• Expertise in data pipeline frameworks such as Airflow, Spark, or Kafka
• Proficiency in cloud platforms including AWS, Azure, or GCP
• Experience with data warehouses such as Snowflake, Redshift, or BigQuery
• Strong SQL and Python skills
• Proven experience handling high-volume enterprise data and complex ETL/ELT processes

Preferred Qualifications

• Experience with financial systems, Accounts Receivable (AR), or ERP-integrated platforms
• Knowledge of remittance and payment reconciliation workflows
• Experience supporting AI/ML data pipelines and feature engineering
• Experience with real-time event-driven architectures and data governance in regulated environments

About the Company

Fractal aims to power every human decision in the enterprise by combining expertise in artificial intelligence, design, engineering, and digital transformation to create cutting-edge solutions for the business world.