Cogentiq
Invoice-to-Cash platform
DataEngineeringLead
Neural analysis suggests this role is
optimal for Lead candidates.
“Data Engineering Lead at Cogentiq. Skills: Data Architecture, Data Pipeline Engineering, Data Quality, Leadership. Define data architecture. Design canonical data models”
What You'll Achieve.
Highly reliable and scalable data pipelines; Accurate financial data reconciliation; Data quality with minimal inconsistencies; AI-ready datasets with high usability; Timely delivery of reporting and analytics
Industry & Context.
Data quality; Data accuracy; Data consistency; Data performance; Data usability
What They're Looking For.
Must Have
Data pipeline frameworks, Airflow, Spark, Kafka, AWS, Azure, GCP, Data warehouses, Snowflake, Redshift, BigQuery, SQL, Python, High-volume enterprise data, Data modeling, ETL/ELT processes
Nice to Have
Financial systems, AR, ERP-integrated platforms, Remittance and payment reconciliation workflows, AI/ML data pipeline support, Real-time event-driven architectures, Data governance in regulated environments
What You'll Do.
Define data architecture
Design canonical data models
Establish data lake/warehouse strategies
Build batch and real-time pipelines
Ensure data transformation
Support structured outputs
Design data pipelines for AI
Ensure high-quality datasets
Implement data validation
Ensure financial data accuracy
Enforce role-based access
Enable KPI dashboards
Support analytics teams
Optimize data availability
How You'll Work.
Team & Collaboration
Lead a team of data engineers; Partner with AI teams; Partner with Integration teams; Partner with ERP teams; Partner with Product teams
Process & Methodology
Drive data roadmap
Full Job Description
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 acce
Applying for this Data Engineering Lead role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Cogentiq?
Real rants from real employees. Read before you apply.