Overview In this role you will lead end-to-end data activation and analytics/engineering initiatives, acting as the connective layer across Studios, Analytics, Finance, Marketing Tech, and engineering teams. You shape roadmaps, clarify goals, and govern dependencies to deliver reliable, scalable data solutions. You'll translate business priorities into executable technical plans and steer cross-functional programs from intake to launch. This position blends program leadership with hands-on data and software fluency in a fast-paced environment.
Compensation / Benefits- medical/dental/vision
- 401(k) with company match
- paid holidays and vacation
- tuition reimbursement
- wellbeing programs
- free games or discounts
Responsibilities- Own end-to-end planning and delivery across data activation, analytics engineering, and data platform integration initiatives
- Lead cross-functional programs across Studios, Analytics, Finance, Marketing Tech, and engineering teams with clear goals, ownership, and success metrics
- Collaborate with engineering and product leadership to shape roadmaps and align team capacity with priorities
- Perform SQL-based validation and first-pass troubleshooting to accelerate issue resolution
- Drive execution across concurrent workstreams, managing milestones, risks, and release coordination
- Understand data flows, schemas, APIs, models, and system integrations to inform decisions
- Establish scalable operating mechanisms for intake, prioritization, status reporting, and governance workflows
- Communicate progress and trade-offs to engineering, business partners, and senior leaders
- Define and track outcomes (adoption, data quality, reliability, timeliness) and continuously improve team collaboration
Key requirements- 7+ years of technical program, product, or project management experience with data, software, platform, or infrastructure engineering
- Hands-on experience as a data analyst/engineer or equivalent technical contributor preferred
- Working proficiency with SQL for schema inspection, output validation, and data quality debugging
- Understanding of the data lifecycle (ingestion, transformation, orchestration, pipelines, APIs, semantic/metrics layers)
- Proven ability to lead complex, cross-functional programs in ambiguous environments
- Excellent written and verbal communication for technical and non-technical audiences
- Strong prioritization, time management, and follow-through with bias for action
- Experience with Jira, Confluence, Slack, M365; comfortable with Scrum, Kanban, or hybrid models
- AI fluency including experience supporting AI/ML programs or using AI tools for planning, QA, or data access
- cross-functional collaboration
- communication clarity
- prioritization and decision-making
- SQL
- data lifecycle understanding
- data platforms/tools (lakehouse, cloud data warehouse)
