Director Data Operations

Role: Director, Data Operations

Job Summary:

The Director, Data Operations is a senior execution and transformation leader responsible for managing and evolving high-throughput, recurring data workflows across internal, offshore, and vendor-supported teams. This role is both a delivery anchor and a transformation agent—ensuring operational excellence today while designing and implementing the intelligent, scalable operations of tomorrow.

Beyond day-to-day workflow management, this role is pivotal in identifying and championing the adoption of new technologies, AI/ML capabilities, automation, and process redesigns. In close partnership with the Data Governance Lead, Operational Excellence Lead, and Program Management, the Data Operations Manager pilots innovations, embeds intelligent automation, and institutionalizes standards that reinforce a culture of accuracy, accountability, and continuous improvement.

Critically, this role is charged with leading the transformation of data operations from a traditional, manual model to an AI-augmented future. This includes enabling intelligent workflows, training operational teams to shift from data entry to AI supervision and validation, and building operational readiness for a future where productivity is scaled not through headcount, but through automation, precision, and agility.

In addition to driving functional outcomes, this role is responsible for leading and developing a high-performing team. The leader will foster a culture of collaboration, continuous learning, and accountability to ensure both business impact and professional growth.

Responsibilities:

• Operational Execution, Leadership, & Delivery Management

• Lead the delivery of operational data workflows across the Ad/Creative Lifecycle including data extraction, transformation, and creation for classification and attribution, and data quality management.
• Manage onshore and offshore teams to meet or exceed SLAs, quality benchmarks, and cycle time expectations.
• Ensure consistency, traceability, and visibility across all workstreams, with robust issue resolution and escalation handling.
• Provide day-to-day leadership, coaching, and mentorship to team members, ensuring clear goals, accountability, and career development.
• Build team capabilities by identifying training needs, encouraging upskilling, and fostering cross-functional collaboration.
• Inspire, motivate, and align the team around organizational goals and vision.
• Drive a positive and inclusive team culture, ensuring strong communication and engagement across levels.

• Vendor Oversight & Accountability Framework

• Oversee daily engagement with third-party vendors executing defined workflows.
• Ensure clarity in what is sent to vendors, how it’s measured, and how results are validated.
• Analyze vendor workload against invoices; identify capacity gaps, inefficiencies, or underperformance.
• Ensure that internal expertise is retained to reduce vendor risk and maintain knowledge resilience.

• Strategic Operational Transformation & Innovation

• Actively identify and recommend new tools, automation, and AI applications that streamline operational workflows.
• Collaborate with the Data Governance and Operational Excellence Leads and Program Management to scope and pilot transformation initiatives.
• Serve as a voice for operational feasibility in transformation projects; contribute to business case development, impact analysis, and implementation.
• Partner with the Operational Excellence Lead and Program Management to reimagine and implement a future-state operating model that replaces manual data entry with AI-supported workflows and intelligent automation.
• Identify and prioritize operational use cases where AI/ML can reduce manual effort, improve quality, and accelerate throughput.
• Lead readiness efforts (training, process change, tooling) to shift operational team focus from task execution to AI validation, supervision, and improvement feedback loops.

• SOPs, Documentation, & Audit Readiness

• Own and maintain documentation of Standard Operating Procedures (SOPs) for all managed workstreams.
• Ensure documentation aligns to frameworks defined by Data Governance and Operational Excellence and includes productivity and quality benchmarks.
• Enforce regular audit cycles and documentation reviews for all internal and vendor-supported work.

• Workflow Planning, Performance Monitoring & Reporting
• Monitor key performance indicators (KPIs) and service metrics to evaluate performance across all delivery teams.
• Support transparency through dashboarding, root cause analysis, and performance reviews.
• Ensure SLA breaches and quality issues are captured, investigated, and addressed with documented actions.
• Contribute to the development of an adaptive team structure that supports AI-augmented workflows, including re-skilling of existing staff and evolving roles.
• Define requirements for new talent profiles (e.g., AI validator, data quality analyst) and coordinate with HR and leadership on workforce planning.
• Partner on change management initiatives that support cultural and behavioral shifts across global data operations teams.
• Collaboration & Enablement
• Partner with Data Governance to ensure alignment to access, quality, and compliance standards.
• Collaborate with the Operational Excellence Lead to support the development and adoption of operational playbooks, automation roadmaps, and improvement plans.
• Participate in OKR definition and tracking with Program Management for operational initiatives.
• Work with Product, Commercial, and Customer Success teams to understand user pain points and business objectives—ensuring operational delivery strategies are designed to meet evolving customer expectations and support data-enabled innovation. 

Success Measures:

• Within 6 Months
• 100% of key workflows documented with SOPs tied to performance metrics and quality benchmarks
• Vendor workloads reconciled with invoice data; gap analysis completed with action plan
• Pilot automation or AI-based improvement initiative scoped and supported
• Baselines established for throughput, quality, and cycle time for top 10 priority processes
• Partnership with OpEx Lead established for improvement planning and support framework
• Develop and publish a transformation plan outlining the evolution from manual data entry to AI-enabled workflows across all core processes.
• Identify and assess at least 2 workflows for transition to AI-supervised delivery models, including risk/impact and retraining needs.
• Within 12 Months

• Operational KPIs trending toward defined targets; measurable improvements in cycle time or quality
• Internal or vendor workflows transformed through automation or tooling adoption
• All SOPs are audit-ready, version-controlled, and maintained
• Operational onboarding and handoff processes are standardized and documented
• Operations supports at least four enterprise-wide initiatives with measurable delivery impact
• Successfully transition at least 30% of high-volume manual workflows to AI-augmented execution with measurable reduction in manual labor.
• ≥75% of impacted team members trained or reassigned to support AI/automation-focused functions with new documentation and SOPs in place.

• Ongoing

• SLA adherence ≥95%; documented processes for exception handling and escalation
• Contribution to enterprise-wide transformation and automation roadmap
• Close partnership maintained with Program Management, Governance, and OpEx to ensure consistency and scalability
• Vendors and internal teams operating with continuous performance tracking, quarterly reviews, and capacity planning
• A culture of operational discipline, data-driven decision-making, and continuous improvement embedded in team practices

Requirements

Qualifications:

• 8–10 years of experience in data operations, shared services, or digital/data delivery roles
• Proven experience in building and leading teams, with a track record of developing talent and elevating team performance.
• Strong interpersonal, coaching, and conflict-resolution skills.
• Ability to create clarity, set direction, and motivate teams in fast-paced environments.
• Experience leading operational transformations involving AI/ML, RPA, or intelligent automation, especially in digital/data-heavy environments.
• Experience managing hybrid teams (onshore/offshore/vendor) in high-volume environments
• Strong process thinking and experience with automation, RPA, or AI/ML initiatives
• Demonstrated experience creating and maintaining SOPs, dashboards, or operational playbooks
• Familiarity with data governance principles, data handling compliance, and audit readiness
• Comfortable working across business and technical teams to drive results
• Tools: Airtable, Smartsheet, Jira, Power BI/Tableau, data automation platforms (preferred)