Data & Analytics Operations Manager

Operational Systems & Delivery

• Own the standards and systems that make work management consistent across the Data & Analytics team - Jira hygiene, project tracking, delivery visibility
• Build the dashboards and reporting that give leaders visibility into overall system health and team throughput
• Own operational workstreams within DNA-wide initiatives - standing up processes, managing dependencies, and tracking delivery

Knowledge, Rituals & Enablement

• Build and maintain DNA's knowledge and context systems (Jira, Confluence, Slack) structured for both human and AI consumption
• Own and/or help facilitate DNA's core team rituals - DNA All Hands, DNA Labs (learning & development), and Data Demos
• Participate in and support DNA's extended leadership team forums
• Build and run onboarding and enablement infrastructure for new DNA team members
• Scale what works - turn high-impact patterns into shared standards, playbooks, and templates

AI-Native Workflows & Tooling

• Design and build AI-powered workflows that eliminate repetitive operational work
• Own DNA's operational tooling ecosystem - continuously optimize, standardize, and drive adoption across teams (Jira, Confluence, Slack workflows, AI tools)
• Lead enablement and upskilling on ways of working within DNA
• Continuously ask: what work here requires human judgment, and what can be automated? Then act on the answer

Qualifications

• 5+ years in data operations, program or project management, platform operations, or a related role with a track record of building systems and tooling
• Deep fluency with AI as a core part of your workflow - you use Claude code or similar instinctively in your own work and know how to design systems that meaningfully leverage it
• Experience working with modern data stack tools (e.g. Tableau, Sigma, Snowflake, Atlan)
• Strong operational judgment applied internally - you approach operational problems with the same rigor as customer-facing ones, with a bias toward simple, scalable solutions
• High data fluency - able to define meaningful metrics, instrument systems, and translate insights into action
• Strong systems thinking - you can distinguish between process issues and structural problems, and know when to optimize vs. redesign
• Clear, direct communication - able to surface what's working and what isn't, and influence across teams, including senior leadership

Nice to Have

• Experience building or scaling a data organization's operating system (e.g., delivery tracking, knowledge management, tooling, onboarding)
• Experience in a high-growth environment, ideally within a regulated domain (fintech, healthcare, HR tech)