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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
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Define and own the end-to-end data architecture.
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Design canonical data models for:
- Remittances
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Payments
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Invoices
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Customers
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Deductions & adjustments
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Branding & template configurations
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Establish scalable data lake/warehouse strategies.
Data Pipeline Engineering
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Build and maintain batch and real-time pipelines ingesting data from:
- ERP systems (SAP, Oracle, NetSuite, etc.)
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Banking systems
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Email ingestion & EDI feeds
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Customer portals & SFTP
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Ensure reliable data transformation, normalization, and enrichment.
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Support structured outputs consumed by AI and integration layers.
Data for AI & Automation
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Design data pipelines that power:
- Intelligent document processing
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Matching & reconciliation models
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Exception detection engines
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Ensure high-quality labeled datasets and feature engineering frameworks.
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Enable feedback loops for model improvement.
Data Quality, Governance & Security
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Implement data validation, reconciliation, and monitoring frameworks.
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Ensure financial data accuracy and consistency across systems.
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Define audit trails, lineage, and compliance controls.
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Enforce role-based access and data security best practices.
Reporting & Analytics Enablement
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Enable KPI dashboards for:
- Auto-match rates
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Exception trends
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Payment reconciliation metrics
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Support analytics for finance and operations teams.
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Optimize data availability for near real-time reporting.
Leadership & Collaboration
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Lead a team of data engineers.
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Partner with AI, Integration, ERP, and Product teams.
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Drive data roadmap aligned with automation and scalability goals.
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Conduct design reviews and enforce data standards.
Required Qualifications
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8–14+ years of experience in data engineering or data architecture.
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Strong expertise in:
- Data pipeline frameworks (Airflow, Spark, Kafka, etc.)
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Cloud platforms (AWS, Azure, GCP)
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Data warehouses (Snowflake, Redshift, BigQuery, etc.)
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SQL and Python
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Experience handling high-volume enterprise data.
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Strong understanding of data modeling and ETL/ELT processes.
Preferred Experience
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Financial systems, AR, or ERP-integrated platforms.
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Remittance and payment reconciliation workflows.
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AI/ML data pipeline support.
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Real-time event-driven architectures.
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Data governance in regulated environments.
Leadership Level
L6– Senior Data Engineering Lead
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Owns execution and reliability of data platform.
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Leads engineering delivery and optimization.
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Ensures data quality and production stability.
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Defines long-term enterprise data architecture.
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Drives cross-product data strategy and governance.
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Influences executive-level data decisions.
What Success Looks Like
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Highly reliable and scalable data pipelines.
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Accurate financial data reconciliation across systems.
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Strong data quality with minimal inconsistencies.
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AI-ready datasets with high usability.
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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!
India: [email protected]
Outside India: [email protected]
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