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Engineering Manager, Data Platform and AI Products

Remote (EST timezone) • Remote • Full-time Contract • Req ID: GDBI-1U3W5R9T

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Engineering Manager, Data Platform and AI Products

Location: Remote (EST preferred) • Type: Full-time • Status: Open
About Global Data and BI Global Data and BI is hiring on a rolling basis for Data, BI & Analytics and ML/AI projects for large corporations. Beyond consulting services, we build production-ready business platforms and SaaS applications that leverage modern cloud technologies, data analytics, and AI capabilities. We deliver enterprise-grade solutions with certified engineers in AWS and Microsoft Azure / Power BI technologies. Our focus includes transformation projects in the financial industry, custom platform development, and our proprietary Noème suite of products. Our mission is to transform the corporate data journey from complexity to strategic clarity, ensuring data is not just collected, but leveraged to drive smarter decisions, stronger businesses, and lasting impact.

Summary

As the Engineering Manager for our Data Platform and AI Products team, you'll lead a team of engineers building the data infrastructure, analytics capabilities, and AI-powered features that power our Noème products and enterprise client solutions. As Global Data and BI scales (supporting enterprise clients with complex data needs) our data platforms and AI capabilities become even more critical. These systems serve as the foundation for everything we deliver, from real-time data pipelines to AI-powered analytics and insights.

You'll guide the team's work on data pipeline architecture, data quality frameworks, AI feature development, experimentation platforms, and the infrastructure that helps us continuously deliver reliable, scalable data solutions. This is a role for someone who is passionate about building great data platforms and AI products, and understands that reliability and data quality are just as important as cutting-edge features.

What you'll do (roles & responsibilities)

  • Build and manage a diverse, inclusive team of 5-8 engineers working on data platforms, AI products, and analytics infrastructure - creating a healthy environment that embodies Global Data and BI's values
  • Recruit, coach, and develop engineers ensuring they receive regular feedback and make progress on personal and professional goals - you don't shy away from performance conversations and recognize the relationship between objective feedback and career growth
  • Set technical direction collaborating closely with cross-functional peers (Product, Data Science, Customer Success) to prioritize work that delivers maximum value to clients and Noème product users
  • Facilitate planning including prioritization, sequencing, and staffing of work - balancing immediate client delivery needs with longer-term platform improvements and AI feature development
  • Ensure accountability keeping the team consistently working on the most important things that deliver value, whether that's meeting client data requirements or building new AI capabilities for Noème products
  • Maintain high quality standards with particular attention to data accuracy, pipeline reliability, system performance, and security/compliance requirements
  • Drive project execution using data to make decisions about prioritization and impact - you have a passion for experimentation and help the team build infrastructure and practices to measure and improve data platform quality
  • Guide technical decisions on data architecture, AI/ML implementations, cloud infrastructure, and technology choices - you have sufficient technical depth to ask the right questions and think through tradeoffs
  • Manage stakeholder relationships working with client teams, internal product managers, and executive leadership to ensure engineering work aligns with business objectives
  • Build team culture fostering collaboration, innovation, continuous learning, and technical excellence
  • Support career development through 1-on-1s, mentorship, performance reviews, and growth opportunities
  • Drive operational excellence ensuring the team has effective processes for code review, testing, deployment, monitoring, and incident response
  • Contribute to engineering practices helping develop Global Data and BI's technical practices, recruiting strategy, onboarding processes, and planning frameworks
  • Champion best practices for data engineering, ML operations, security, and compliance across the organization
  • Lead by example demonstrating technical excellence, clear communication, and commitment to company values

What you should have (Must-Haves)

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field
  • 2+ years of experience managing engineering teams working on data platforms, data engineering, or AI/ML products
  • Deep understanding of what it takes to build and maintain high-quality data platforms at scale - handling millions of records, thousands of data pipelines, and enterprise compliance requirements
  • Sufficiently deep technical background in data engineering, cloud platforms, and AI/ML to guide team members, review architectures, and make informed technical decisions
  • Understanding that data platforms are mission-critical infrastructure - you're excited about the work even when it involves data quality fixes and reliability improvements, not just cutting-edge ML features
  • Experience with modern data stack including data warehouses/lakes/lakehouses, ETL/ELT tools, orchestration platforms, and analytics engines
  • Knowledge of cloud platforms (AWS and/or Azure) and infrastructure for data workloads
  • Strong people management skills - you create team environments that are collaborative, empowering, supportive, and challenging where engineers do their best work
  • Excellent communication skills - empathetic and direct, enabling you to give and receive feedback effectively and create alignment cross-functionally
  • High tolerance for ambiguity and change - you enjoy jumping into areas that need attention and learning as you go
  • Passion for line management and building strong, cohesive team culture
  • Business acumen - understanding how engineering work connects to client value and business outcomes
  • Project management skills - ability to coordinate complex projects across multiple teams and stakeholders
  • Experience with agile methodologies and iterative development practices

Nice-to-Haves

  • Experience with AI/ML products including building features powered by LLMs, embeddings, or traditional ML models
  • Knowledge of data governance and compliance frameworks (GDPR, SOC 2, HIPAA) for enterprise data platforms
  • Experience with real-time data systems including streaming platforms (Kafka, Kinesis, Event Hubs) and CDC patterns
  • Background in consulting or professional services organizations managing client delivery teams
  • Experience with BI platforms (Power BI, Tableau, Looker) and analytics product development
  • Understanding of financial services or regulated industries and their data requirements
  • Experience building experimentation platforms and A/B testing frameworks for data-driven decision making
  • Knowledge of modern data tools (dbt, Airflow, Dagster, Databricks, Snowflake, Synapse)
  • Experience with MLOps and productionizing ML models at scale
  • Background managing teams during rapid growth and organizational change
  • Experience rolling out engineering practices (code review, performance reviews, technical ladders) where they didn't exist before
  • Contributions to open source data or ML projects
  • Technical certifications in AWS, Azure, or data platforms
  • Experience with data quality frameworks (Great Expectations, Monte Carlo, deequ)
  • Understanding of vector databases and semantic search for AI applications
  • Bilingual proficiency in English and French (asset for managing bilingual engineering teams and supporting Quebec clients)

Work details

  • Location: Remote (EST timezone preferred for collaboration with teams and clients)
  • Reporting relationship: You will report to the Director of Engineering, VP of Engineering, or Chief Technology Officer

Compensation

Competitive engineering management salary package adjusted to your local market and country of residence. Compensation is location-based and reflects regional market standards. We benchmark against leading technology companies in your country to ensure competitive, fair pay for engineering managers with data platform and AI product expertise.

Our commitment to diversity, equity, and inclusion We're committed to employment equity and encourage women, Indigenous Peoples, persons with disabilities, veterans and persons of all races, ethnicities, religions, abilities, sexual orientations, and gender identities and expressions to apply. We also welcome applications from Latin America countries, as the position is remote.

What happens after you apply

Timeline: We aim to complete our process within 2-3 weeks of application.

Step 1
Apply Submit your application. If you applied before and were not successful, you are welcome to apply again.
Step 2
Initial call (1 hour) If pre-selected, we schedule an initial conversation.
Step 3
Leadership interview (1h30) If shortlisted, covering management philosophy, team building, and technical leadership.
Step 4
Technical discussion (1h30) Deep dive on data platform architecture, AI products, and engineering practices.
Step 5
Panel interview (1h30) Meet with Engineering Leadership, Product, and cross-functional stakeholders.
Step 6
Hiring decision If selected, we send an offer and next steps, otherwise we inform you by email.
If you don't hear back from us after application or any interview stage, it means we do not pursue your application.
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