POS Integration & Implementation Engineer – Retail Data

Location: Toronto, Ontario, Canada (Hybrid/Remote, depending on business requirements) - Daisyintelligence.com

Position Overview

We are seeking an experienced POS Integration & Implementation Engineer to lead technical integrations between Daisy Retail and third-party POS systems.

The ideal candidate will have strong experience in SQL, REST APIs, ETL processes, retail data integration, and customer-facing technical implementations.

This individual will work closely with POS technology partners, retail customers, and Daisy's internal engineering and AI teams to establish reliable data connections, automate data synchronization, and ensure successful customer onboarding.

Key Responsibilities

1. POS Systems Integration

• Lead technical integrations with retail POS systems and technology partners.
• Work with POS vendors to understand their APIs, database schemas, data formats, and integration capabilities.
• Establish secure data connections between retailers' POS systems and Daisy Retail.
• Integrate sales transactions, product catalogs, SKU/UPC information, pricing, promotions, inventory, and store-level data.
• Support API-based, database-based, and file-based integrations depending on POS vendor capabilities.
• Develop reusable integration frameworks to accelerate onboarding of new POS partners and retailers.

2. SQL & Database Integration

• Develop and optimize complex SQL queries, joins, CTEs, views, and stored procedures.
• Extract and transform retail transaction, pricing, inventory, and product data.
• Work with Microsoft SQL Server, PostgreSQL, MySQL, or equivalent relational databases.
• Perform data reconciliation, validation, and troubleshooting.
• Optimize database queries and data extraction processes for performance and scalability.
• Investigate missing, duplicated, inconsistent, or delayed POS data.

3. API & ETL Development

• Develop and maintain integrations using REST APIs, JSON, XML, CSV, and SFTP.
• Build and maintain ETL/ELT pipelines for automated data extraction, transformation, and loading.
• Develop Python scripts for data processing, automation, and integration workflows.
• Implement scheduled and incremental data synchronization.
• Handle API authentication, pagination, rate limits, retries, and error handling.
• Monitor integration performance and resolve synchronization failures.

4. Retail Data Mapping & AI Platform Integration

• Map POS data fields to Daisy Retail's standardized data model.
• Ensure accurate ingestion of sales, pricing, promotions, product, and inventory information.
• Work with Daisy's AI and analytics teams to understand data requirements for price optimization and promotional recommendations.
• Validate historical and ongoing data feeds to support AI analysis.
• Maintain data consistency across multiple stores, POS systems, and retail customers.
• Support onboarding of new retail data sources as Daisy expands its AI capabilities.

5. Customer Onboarding & Technical Implementation

• Manage technical implementation after POS partnerships are established.
• Conduct technical discovery sessions with POS partners and retail customers.
• Gather integration requirements and assess technical feasibility.
• Configure and test data integrations for new retail customers.
• Coordinate user acceptance testing, production deployment, and go-live activities.
• Provide technical troubleshooting and post-implementation support.
• Collaborate with internal engineering, product, customer success, and business development teams.

6. Data Security, Monitoring & Documentation

• Implement secure data transfer, encryption, and credential management.
• Follow least-privilege access principles for POS databases and APIs.
• Maintain integration logs, monitoring, alerts, and audit trails.
• Document API specifications, database mappings, integration workflows, and troubleshooting procedures.
• Ensure reliable and scalable integration architecture.

Required Technical Skills

SQL & Databases — Mandatory

• Advanced SQL, including complex joins, CTEs, aggregations, and window functions.
• Microsoft SQL Server (T-SQL), PostgreSQL, or MySQL.
• Query optimization, stored procedures, views, and data reconciliation.
• Experience working with large transactional datasets.

API Integration — Mandatory

• REST APIs, JSON, XML, and HTTP.
• OAuth 2.0, API keys, and token-based authentication.
• Postman or equivalent API testing tools.
• API pagination, rate limiting, retries, and error handling.

Data Engineering & ETL — Mandatory

• ETL/ELT pipeline development.
• Python for data extraction, transformation, and automation.
• CSV, JSON, XML, and SFTP data integration.
• Data mapping, validation, and synchronization.

Retail POS Systems — Mandatory

• Hands-on experience integrating POS systems or retail transaction platforms.
• Understanding of sales transactions, SKUs, UPCs, product catalogs, pricing, discounts, promotions, returns, and inventory.
• Experience working with multi-store retail environments.
• Familiarity with POS platforms such as NCR, Lightspeed, Shopify POS, Oracle Retail, Square, or similar solutions.

Cloud & Development Tools — Preferred

• Microsoft Azure or AWS.
• Git and CI/CD fundamentals.
• Cloud-based data pipelines and scheduled jobs.
• Logging, monitoring, and automated testing.

Nice-to-Have Experience

• Grocery, supermarket, or multi-location retail technology.
• Retail pricing and promotion management systems.
• Electronic shelf label (ESL) integrations.
• Retail analytics or AI-powered SaaS platforms.
• Experience integrating multiple POS vendors into a standardized data platform.

Key Success Measures

• Successful onboarding of new POS partners and retail customers.
• Accurate and timely delivery of retail data into Daisy Retail.
• Reduced integration implementation timelines.
• Minimal data synchronization failures.
• High data quality and reliable integration performance.
• Reusable integration processes that support business growth.