Caseware is one of Canada's original Fintech companies, having led the global audit and accounting software industry for over 30 years, with more than 500,000 users across 130 countries and available in 16 different languages. While you might not have heard of us (yet) over 36,000 accounting and audit professionals list Caseware as a skill on their LinkedIn profiles!
As part of our continued evolution of Caseware Cloud, we are building a shared, enterprise-grade Data Platform that serves as the foundation for analytics, AI-powered experiences, and system interoperability across our SaaS ecosystem.
This platform owns data ingestion and ETL from internal and external systems, data cleansing, quality management,data lake architecture, and data security and governance. These capabilities power Caseware’s analytics and AI features in the cloud while also enabling third-party and customer-managed data integrations.
We are looking for a Software Development Manager (Level IV) to lead teams building and operating this Data Platform. In this role, you will be responsible for people leadership, delivery execution, and technical stewardship of a platform that is foundational to Caseware’s cloud strategy. You will lead delivery of the platform’s product and technical roadmap, ensuring the architecture scales reliably, performs efficiently, and evolves to meet the needs of product teams, customers, and partners over time.
📍 Location: This is a fully remote position located in Colombia.
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What you will be doing
- Lead delivery of the Data Platform product and technical roadmap, guiding architecture and execution to ensure the platform scales reliably, performs efficiently, and continues to meet the evolving needs of customers and partners.
- Lead, coach, and grow a team of data and platform engineers responsible for building and operating the Data Platform.
- Collaborate with Product, domain SMEs, and downstream consumers to translate business and customer needs into clear platform roadmaps and delivery plans
- Provide technical leadership by guiding architectural decisions, reviewing designs, and ensuring implementations align with platform standards and long-term maintainability
- Ensure the Data Platform meets observability, privacy, security, and compliance requirements, working closely with QA, Security, and Compliance teams
- Drive operational excellence, including incident response, post-mortems, and continuous improvement of data freshness, accuracy, reliability, performance, and cost efficiency
- Partner with DevOps and DevSuccess to improve CI/CD pipelines, deployment practices, monitoring, and alerting for data systems
- Actively manage and reduce technical debt, balancing near-term delivery with long-term platform health
- Hire, onboard, and develop engineers, providing coaching, feedback, performance management, and career development support
- Serve as an escalation point for complex delivery, operational, or technical issues, helping teams navigate ambiguity and make sound trade-offs
What you’ll bring
- 4+ years of people management experience leading software or data engineering teams
- 8+ years of professional engineering experience, with a strong background in data engineering, platform systems, or distributed systems
- Experience leading teams that build and operate data ingestion pipelines, ETL workflows, and cloud-based data platforms
- Solid understanding of data lake architectures, data quality practices, metadata/cataloging systems, and data governance
- Experience delivering cloud-native systems on AWS, with awareness of scalability, reliability, security, and cost trade-offs
- Strong communication and leadership skills, with the ability to align engineers and stakeholders around shared outcomes
- Strong English language communication and collaboration skills
- Operate with an AI-first mindset, leveraging tools to enhance productivity, decision-making, and day-to-day work.
- Champion a culture of AI experimentation — proactively explore, adopt, and share emerging tools relevant to your role.
- Integrate AI tools into daily workflows to automate repetitive tasks, accelerate outputs, and improve overall efficiency.
- Use AI-assisted tools to enhance drafting, summarization, research, and data analysis tasks.
- Apply critical thinking to validate and refine AI-generated outputs, ensuring accuracy, relevance, and alignment with quality standards.
- Recognize the limitations of AI tools and exercise independent judgment on all AI-assisted work before sharing or acting on results.
- Continuously build AI fluency — including foundational prompt engineering skills — to maximize the quality and reliability of AI outputs.
Nice to have
- Experience operating platforms in regulated or compliance-heavy environments
- Familiarity with accounting, auditing, or financial workflows
- Experience supporting partner ecosystems or customer-managed data integrations
