Head of Data Systems

The Head of Data Systems (Google Stack) will play a key role at Stacktics, required to help create and maintain industry-leading quality and efficiency of service and software delivery. Stacktics will rely on the Head of Data Systems with ownership of the Data Systems function including mentoring and support for our team of engineers, developers, marketing analysts and data scientists. The successful candidate will be expected to meet and exceed Stacktics’ quality standards, while helping the organization rapidly expand into increasingly complex application development, data engineering, and related workflows.

KEY RESPONSIBILITIES
Ownership of Stacktics’ Data Systems Business Unit
- Build and grow your team’s capabilities and expertise to be truly platform-agnostic, ever-adapting based on opportunity and business direction
- Lead thorough audits of clients'/prospects' Data Systems, and other associated platforms and technologies as applicable including performance and cloud cost-efficiency
- Provide proactive recommendations, identifying areas of opportunity and/or improvement for clients based on their underlying business objectives and goals
- Maintain continuous focus on work output quality and reliability, acting as the champion of customer satisfaction in a proactive manner and as the final escalation point for technical and delivery issues that cannot be resolved at the Technical Lead level
- Act as Stacktics’ primary Data Systems expert, ensuring to maintain and continuously grow personal expertise, and sharing information with other Stacktics team members, client stakeholders and prospects
- Collaborate with, support, and work closely with cross-functional units to ensure efficient workflow, and realize cross-functional opportunities and enhancements
- Maintain responsibility for the Business Unit’s growth and success, continuously developing existing engagements, optimizing resourcing and prospecting
- Be dedicated to the success and happiness of your team members, optimizing workflow, enabling their personal growth, and acting as a strong team leader overall Instilling Development Best Practices and Skills/Procedures Advancement
- Establishing, maintaining and evolving DevSecOps best practices and tools, and continuously keeping them aligned with current industry best practices and procedures
- Understanding, implementing and automating security controls, governance processes, and compliance validation frameworks
- Contributing to deployment tooling within the Stacktics team
- Contributing to version control technology frameworks and creating/implementing working processes within the Data Systems team, with tools such as Git or SVN
- Own and continuously improve the practice’s AI coding standards, the AI coding constitution (CLAUDE.md, GEMINI.md, .cursorrules), PR checklists, and slash commands keeping them current as tools, clients, and the team’s needs evolve Leading in the Software 3.0 Era AI tools have changed how fast engineering work gets produced. Your job is to make sure that speed shows up as sounder architecture and higher-quality delivery — not just faster shipping of the same judgment gaps.
- Recalibrate how the team scopes and estimates work as AI tooling changes what can actually be delivered in a sprint, so timelines and resourcing plans reflect real AI-era delivery speed
- Set architecture and coding standards that assume engineers are using AI assistants daily — code review habits, eval frameworks, and quality gates sized to the failure modes of AI-assisted development, not just its speed
- Continue evolving Stacktics’ AI Development Lifecycle (ADLC) — our AI-native answer to SDLC — piloting new stages against real engagements and driving adoption across the team
- Be an active daily user of AI coding assistants yourself, and bring that firsthand experience into how standards and review practices are set for the team
- Lead Stacktics’ technical team members through the integration into Agentic AI-first working patterns, and beyond Code Productization
- Migrating the delivery of the most common/universally applicable solutions from custom projects to formally productized software solutions
- Advocating for building repeatability, scalability and standardization into how the Stacktics Data Systems team approaches all work, in order to enable the future migration to productization as a general rule Data Engineering-Specific Responsibilities
- Participate in continuous delivery pipelines to fully automate deployment of the highly available cloud platform that supports multiple projects
- Design and develop ETL workflows and datasets to be used in data visualization tools
- Write complex SQL queries with multiple joins to automate and manipulate data extracts
- Perform end to end Data Validation to maintain accuracy of data sets
- Build tools for deployment, monitoring and operations
- Troubleshoot and resolve issues in the development, test and produc