About MediaRadar: MediaRadar , now including the data and capabilities of Vivvix, powers the mission-critical marketing and sales decisions that drive competitive advantage. Our competitive advertising intelligence platform enables clients to achieve peak performance with always-on data and insights that span the media, creative, and business strategies of five million brands across 30+ media channels. By bringing the advertising past, present, and future into focus, our clients rapidly act on the competitive moves and emerging advertising trends impacting their business. Job Summary: The proactive and technically skilled Automation Specialist, will implement, and maintain automation solutions that improve the efficiency, accuracy, and scalability of our data operations workflows. This role will leverage Robotic Process Automation (RPA), APIs, low-code/no-code tools, and other automation technologies to reduce manual effort, eliminate redundancies, improve data lifecycle management, and enhance data quality. The ideal candidate is both hands-on and strategic, capable of identifying automation opportunities and delivering impactful, scalable solutions in partnership with data, engineering, and business teams. Responsibilities: Automation Strategy & Execution Partner with data engineers, analysts, governance leads, and business SMEs to understand requirements and build fit-for-purpose solutions that include data ingestion, transformation, validation, quality monitoring, and reporting. Design, build, and maintain automation solutions using RPA platforms (e.g., Blue Prism, UiPath, Automation Anywhere, Power Automate) and workflow orchestration tools. Develop and deploy APIs, scripts, and connectors to automate data exchange across systems. Workflow Optimization Utilize current-state workflow maps and identify inefficiencies, bottlenecks, and error-prone processes. Collaborate with stakeholders to re-engineer and streamline data operations processes. Ensure automations are optimized for performance, scalability, and maintainability. Governance & Documentation Maintain thorough documentation of automation processes, logic, and dependencies. Ensure compliance with data governance, quality, and security policies. Build in auditability, alerts, and failover procedures to support data reliability. Educate and upskill data operations and business teams on automation best practices and tool usage and what’s possible. Monitoring & Continuous Improvement Working with Data Office leadership, establish and track KPIs to measure automation impact (time saved, error reduction, etc.). Monitor performance and reliability of automation solutions, iterating as needed. Stay current with emerging automation tools and techniques to continually improve capabilities. Success Measures: Within 6 Months Deliver a minimum of 3 high-effort manual data processes automated and running in production delivering at least 10% reduction in manual effort across the team. Create an automation pipeline that is monitored and documented with measurable time and error reductions allowing for effective prioritization and impact. A framework for identifying, prioritizing, and documenting automation opportunities is established. Within 12 Months At least 30–40% reduction in manual effort across targeted workflows. 80% of routine data validation and quality checks are automated and integrated into the data operations workflow. Documentation and alerting in place for all automated workflows, ensuring transparency and traceability. Ongoing Automation backlog is regularly reviewed and prioritized in collaboration with stakeholders. Time saved, errors reduced, and capacity increased are consistently reported as impact metrics. New automation opportunities are surfaced through ongoing collaboration with governance, engineering, and business teams. Requirements 4–6 years of experience in automation, data operations, or process engineering. Hands-on experience with RPA tools (e.g., UiPath, Blue Prism, Automation Anywhere) and scripting languages (Python, PowerShell, etc.). Familiarity with data pipelines, APIs, and integration tools. Knowledge of data quality, governance, and lifecycle management. Strong problem-solving, documentation, and stakeholder communication skills. Show more Show less

About MediaRadar: MediaRadar , now including the data and capabilities of Vivvix, powers the mission-critical marketing and sales decisions that drive competitive advantage. Our competitive advertising intelligence platform enables clients to achieve peak performance with always-on data and insights that span the media, creative, and business strategies of five million brands across 30+ media channels. By bringing the advertising past, present, and future into focus, our clients rapidly act on the competitive moves and emerging advertising trends impacting their business. Job Summary: The proactive and technically skilled Automation Specialist, will implement, and maintain automation solutions that improve the efficiency, accuracy, and scalability of our data operations workflows. This role will leverage Robotic Process Automation (RPA), APIs, low-code/no-code tools, and other automation technologies to reduce manual effort, eliminate redundancies, improve data lifecycle management, and enhance data quality. The ideal candidate is both hands-on and strategic, capable of identifying automation opportunities and delivering impactful, scalable solutions in partnership with data, engineering, and business teams. Responsibilities : Automation Strategy & Executi onPartner with data engineers, analysts, governance leads, and business SMEs to understand requirements and build fit-for-purpose solutions that include data ingestion, transformation, validation, quality monitoring, and reportin g.Design, build, and maintain automation solutions using RPA platforms (e.g., Blue Prism, UiPath, Automation Anywhere, Power Automate) and workflow orchestration tool s.Develop and deploy APIs, scripts, and connectors to automate data exchange across system s.Workflow Optimizati onUtilize current-state workflow maps and identify inefficiencies, bottlenecks, and error-prone processe s.Collaborate with stakeholders to re-engineer and streamline data operations processe s.Ensure automations are optimized for performance, scalability, and maintainabilit y.Governance & Documentati onMaintain thorough documentation of automation processes, logic, and dependencie s.Ensure compliance with data governance, quality, and security policie s.Build in auditability, alerts, and failover procedures to support data reliabilit y.Educate and upskill data operations and business teams on automation best practices and tool usage and what’s possibl e.Monitoring & Continuous Improveme ntWorking with Data Office leadership, establish and track KPIs to measure automation impact (time saved, error reduction, etc. ).Monitor performance and reliability of automation solutions, iterating as neede d.Stay current with emerging automation tools and techniques to continually improve capabilitie s. Success Measur es:Within 6 Mon thsDeliver a minimum of 3 high-effort manual data processes automated and running in production delivering at least 10% reduction in manual effort across the te am.Create an automation pipeline that is monitored and documented with measurable time and error reductions allowing for effective prioritization and impa ct.A framework for identifying, prioritizing, and documenting automation opportunities is establish ed.Within 12 Mon thsAt least 30–40% reduction in manual effort across targeted workflo ws.80% of routine data validation and quality checks are automated and integrated into the data operations workfl ow.Documentation and alerting in place for all automated workflows, ensuring transparency and traceabili ty.Ongo ingAutomation backlog is regularly reviewed and prioritized in collaboration with stakeholde rs.Time saved, errors reduced, and capacity increased are consistently reported as impact metri cs.New automation opportunities are surfaced through ongoing collaboration with governance, engineering, and business tea ms. Requirem ents 4–6 years of experience in automation, data operations, or process enginee ring.Hands-on experience with RPA tools (e.g., UiPath, Blue Prism, Automation Anywhere) and scripting languages (Python, PowerShell, e tc.).Familiarity with data pipelines, APIs, and integration t ools.Knowledge of data quality, governance, and lifecycle manage ment.Strong problem-solving, documentation, and stakeholder communication sk ills.