Data Implementation Manager

Odaia Intelligence Inc.•,

1d•Remote

About The Position

As Data Implementation Manager you will lead a team responsible for configuring, implementing, and optimizing our AI-driven platform for customers. You will oversee technical solution delivery, drive process improvements, and ensure seamless customer onboarding and integration. Reporting to the Director, Data Management you will act as a key liaison between technical teams and customers, ensuring smooth deployments and high-quality data processing.

Requirements

Leadership experience in managing technical teams, particularly in software implementation, customer onboarding, or data integration.
Strong technical foundation: proficiency in Python, SQL, and cloud platforms (AWS preferred)
Expertise in ETL and data integration with large data technologies such as PySpark and Snowflake
Experience working with APIs and integration frameworks to connect platforms and automate data flows
Familiarity with industry-specific tools such as Veeva Vault, Salesforce, and other CRM or data management platforms
Exceptional problem-solving skills with a customer-centric mindset, ensuring a seamless experience for clients
Excellent communication and stakeholder management skills, able to bridge the gap between technical and non-technical teams

Responsibilities

Lead and mentor a team of Technical Implementation Specialists, providing guidance and best practices for seamless customer deployments
Oversee customer onboarding and technical implementations, ensuring a smooth transition and system integration
Collaborate with clients and internal teams to define technical requirements and tailor solutions to their needs
Design and optimize ETL workflows, leveraging automation and AI agents to ensure repeatable, high-quality, and cost-efficient recurring data deliveries
Manage integration of customer data into ODAIA’s platform, ensuring accuracy and performance
Oversee data ingestion and pipeline configuration to ensure optimal data readiness for ODAIA's commercial intelligence and AI models.
Utilize modern data tools (e.g., PySpark, Snowflake) to explore, troubleshoot, and resolve issues with ETL and system configuration
Ensure timely and high-quality data deliveries, maintaining data integrity and compliance with industry standards
Analyze team performance data and team output KPIs to identify bottlenecks, improve implementation processes and increase automation
Drive cross-functional collaboration, ensuring alignment between customer success, engineering, and product teams