The Opportunity

Full-Time • Permanent • Hybrid (3 Days On-Site / 2 Remote)

A growing payments technology company is seeking a Data Platform Manager to lead the team responsible for building and operating its data platform. You'll set technical direction, own platform strategy and oversee systems that support payment processing, risk management, analytics and AI capabilities across the business. This role combines engineering leadership, production ownership and responsible AI innovation within a regulated payments environment.

What You'll Do

- Lead, coach and develop the Data Platform team, establishing standards for engineering quality, design, code review, documentation and delivery.
- Define the platform's technical direction and roadmap, aligning priorities with business objectives, operational needs and risk requirements.
- Own the end-to-end data platform, including ELT pipelines, real-time data processing, data warehousing and self-service access to trusted data.
- Oversee production data systems supporting critical business operations, including payment processing, risk management and marketing platforms.
- Ensure platform scalability, performance, reliability and operational excellence across data infrastructure.
- Translate complex business and technical challenges into clear priorities, milestones and execution plans.
- Balance delivery commitments with platform investments, technical debt, governance and long-term infrastructure health.
- Establish monitoring, incident response and operational practices to maintain reliable production data services.
- Build and expand data products, services and AI agents that make organizational data accessible and useful across business functions.
- Advance MLOps and AI Gateway infrastructure to support the deployment and operation of production machine learning models.
- Extend AI-assisted and agentic engineering practices across the team,



establishing appropriate standards and safeguards.
- Automate data governance processes covering data quality, privacy, security and access controls.
- Ensure data platform practices align with PCI-DSS and applicable privacy requirements, including controls over AI agent access to data.
- Identify architecture risks, technical debt and governance gaps before they affect platform performance or business operations.
- Partner with leadership, Risk, Compliance and technical stakeholders to communicate roadmap decisions, manage dependencies and secure alignment.

What We Are Looking For

- 7+ years of experience in data engineering, analytics engineering, software engineering or a related technical field.
- 2+ years of experience leading and developing technical teams.
- Proven ability to lead teams that balance business delivery with operational excellence.
- Strong experience designing, building and operating production-grade data pipelines and platform infrastructure.
- Experience deploying data products, machine learning models or AI capabilities into production.
- Robust understanding of analytics engineering, including data modelling, version control, testing, CI/CD and documentation.
- Strong knowledge of data warehousing, ELT architecture and data governance.
- Proficiency in SQL and Python or comparable programming languages.
- Experience leading complex technical projects from discovery through implementation and production delivery.
- Working knowledge of how AI agents and LLM applications access and consume data,



including tool interfaces, MCP, semantic layers and access controls.
- Hands-on experience using AI coding tools such as Claude Code, Cursor or comparable development agents.
- Strong technical judgment and ability to make architecture trade-offs involving scalability, performance, security and maintainability.
- Proven ability to coach engineers, conduct meaningful code reviews and establish clear technical standards.
- Strong stakeholder management skills, including the ability to influence leadership, Risk and Compliance teams.
- Ability to establish responsible AI practices, recognizing where automation is appropriate and where human review is essential.

Additional Technical Assets

- Experience with Google Cloud Platform, BigQuery, dbt and Airflow.
- Experience building agentic workflows, IDE specifications or skills that automate data pipeline development.
- Experience developing MCP servers or other interfaces that expose governed data to AI agents.
- Hands-on experience with Docker or Kubernetes for data applications and MLOps workflows.
- Experience with Kafka or similar streaming technologies.
- Familiarity with observability platforms such as Datadog.
- Experience with Metabase or other business intelligence and self-service analytics tools.
- Background supporting risk management, fraud detection or machine learning use cases.
- Experience in payments, fintech or other regulated financial environments.

Why Join

Lead a data platform with direct impact on payment processing, risk management and AI innovation. Shape engineering strategy, develop a high-performing team and build scalable infrastructure while advancing responsible AI capabilities across a growing payments organization.

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📌 Data Platform Manager (Calgary)
🏢 Impact Logic
📍 Calgary