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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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