Director, Data Operations
MediaRadar, Inc.
full-time
Posted on:
Location Type: Hybrid
Location: Vadodara • 🇮🇳 India
Visit company websiteJob Level
Lead
Tech Stack
RPATableau
About the role
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Requirements
- 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)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data extractiondata transformationdata quality managementAI/MLRPAautomationSOP creationdashboardingperformance metricsoperational playbooks
Soft skills
leadershipcoachingconflict resolutionteam motivationcommunicationcross-functional collaborationissue resolutionaccountabilitymentorshiporganizational alignment