It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
We are looking for a highly experienced
Data Engineering Lead
to build and scale the data foundation of our Intelligent Invoice-to-Cash (I2C) platform. The platform powers Invoice Template Creation (Branding), Remittance ingestion, Payments reconciliation, AI-based Cash Application, and ERP posting.
You will lead the design and development of robust, scalable, and secure data pipelines that unify multi-source financial data into reliable, analytics-ready and AI-ready datasets. This is a strategic leadership role responsible for ensuring data quality, availability, governance, and performance across the platform.
Key Responsibilities
Data Architecture & Platform Design
Define and own the end-to-end data architecture.
Design canonical data models for:
Remittances
Payments
Invoices
Customers
Deductions & adjustments
Branding & template configurations
Establish scalable data lake/warehouse strategies.
Data Pipeline Engineering
Build and maintain batch and real-time pipelines ingesting data from:
ERP systems (SAP, Oracle, NetSuite, etc.)
Banking systems
Email ingestion & EDI feeds
Customer portals & SFTP
Ensure reliable data transformation, normalization, and enrichment.
Support structured outputs consumed by AI and integration layers.
Data for AI & Automation
Design data pipelines that power:
Intelligent document processing
Matching & reconciliation models
Exception detection engines
Ensure high-quality labeled datasets and feature engineering frameworks.
Enable feedback loops for model improvement.
Data Quality, Governance & Security
Implement data validation, reconciliation, and monitoring frameworks.
Ensure financial data accuracy and consistency across systems.
Define audit trails, lineage, and compliance controls.
Enforce role-based access and data security best practices.
Reporting & Analytics Enablement
Enable KPI dashboards for:
Auto-match rates
Exception trends
Payment reconciliation metrics
Support analytics for finance and operations teams.
Optimize data availability for near real-time reporting.
Leadership & Collaboration
Lead a team of data engineers.
Partner with AI, Integration, ERP, and Product teams.
Drive data roadmap aligned with automation and scalability goals.
Conduct design reviews and enforce data standards.
Required Qualifications
8–14+ years of experience in data engineering or data architecture.
Strong expertise in:
Data pipeline frameworks (Airflow, Spark, Kafka, etc.)
Cloud platforms (AWS, Azure, GCP)
Data warehouses (Snowflake, Redshift, BigQuery, etc.)
SQL and Python
Experience handling high-volume enterprise data.
Strong understanding of data modeling and ETL/ELT processes.
Preferred Experience
Financial systems, AR, or ERP-integrated platforms.
Remittance and payment reconciliation workflows.
AI/ML data pipeline support.
Real-time event-driven architectures.
Data governance in regulated environments.
Leadership Level
L6– Senior Data Engineering Lead
Owns execution and reliability of data platform.
Leads engineering delivery and optimization.
Ensures data quality and production stability.
Defines long-term enterprise data architecture.
Drives cross-product data strategy and governance.
Influences executive-level data decisions.
What Success Looks Like
Highly reliable and scalable data pipelines.
Accurate financial data reconciliation across systems.
Strong data quality with minimal inconsistencies.
AI-ready datasets with high usability.
Timely delivery of reporting and analytics.
Why Join Us?
You will build the data backbone of a next-generation Invoice-to-Cash platform that transforms enterprise finance through automation, AI, and scalable architecture.
If you are passionate about building high-impact data platforms in financial systems, we would love to connect.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Hiring Related Queries
India:
HiringsupportIndia@fractal.ai
Outside India:
HiringsupportROW@fractal.ai
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