Job Description
We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that’s bold, industrious, and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration, and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com Looking to jump-start your career? We understand how important the first few years of your career are, which create the foundation of your entire professional journey. At Indegene, we promise you a differentiated career experience. You will not only work at the exciting intersection of healthcare and technology but also will be mentored by some of the most brilliant minds in the industry. We are offering a global fast-track career where you can grow along with Indegene’s high-speed growth. We are purpose-driven. We enable healthcare organizations to be future ready and our customer obsession is our driving force. We ensure that our customers achieve what they truly want. We are bold in our actions, nimble in our decision-making, and industrious in the way we work.
We are looking for a highly skilled Lead Engineer who can bridge the gap between business, analytics, and technology. The ideal candidate will have strong expertise in digital analytics implementation, tag management, reporting, and data-driven decision-making while also driving innovation through Generative AI and automation use cases.
This is a client-facing leadership role that requires a blend of technical expertise, consulting skills, stakeholder management, and solution-oriented thinking. The candidate will be responsible for defining measurement strategies, leading analytics implementations, generating actionable insights, identifying optimization opportunities, and building next-generation AI-powered solutions to improve efficiency and business outcomes.
Must Have
Key Responsibilities
Analytics Strategy & Implementation
• Lead end-to-end analytics implementation planning across web, mobile, and digital platforms
• Define measurement frameworks, KPIs, and tracking strategies aligned with business objectives
• Translate business requirements into scalable tracking specifications, data layers, and implementation plans
• Oversee implementation and governance of analytics solutions using GTM, Tealium, GA4, Adobe Analytics, and related platforms
• Ensure data quality through robust QA processes, monitoring, and validation frameworks
Tag Management & Data Collection
• Design, implement, and maintain client-side and server-side tagging solutions
• Manage third-party marketing, advertising, and analytics platform integrations
• Optimize tracking architecture for performance, scalability, and compliance
• Drive consent management and privacy-compliant data collection strategies
• Establish implementation standards, governance models, and best practices
Reporting & Insights
• Develop executive dashboards and performance reporting frameworks
• Analyze digital performance and user journeys to identify optimization opportunities
• Generate actionable insights across marketing, customer experience, content engagement, and campaign effectiveness
• Work with business stakeholders to define success metrics and translate data into business recommendations
• Support experimentation, attribution, audience analysis, and measurement strategies
### Generative AI & Innovation
• Identify, design, and implement Generative AI use cases across analytics, reporting, implementation, and operational workflows
• Build AI-powered solutions to automate QA, documentation, reporting, tagging validation, and anomaly detection
• Evaluate emerging AI technologies and assess applicability for client business challenges
• Create proof-of-concepts, accelerators, and reusable frameworks that enhance team productivity
• Drive a culture of innovation by evangelizing AI adoption across teams and clients
Client Consulting & Stakeholder Management
• Serve as a trusted advisor to clients on analytics, measurement, and data strategy
• Lead discovery workshops, solutioning discussions, and implementation planning sessions
• Present recommendations, insights, and strategic roadmaps to client stakeholders
• Collaborate with marketing, product, engineering, media, and business teams to deliver integrated solutions
• Manage multiple workstreams while ensuring delivery excellence and customer satisfaction
Team Leadership & Capability Building
• Mentor and guide engineers, analysts, and consultants
• Review solution designs, implementation approaches, and deliverables
• Drive capability development in analytics, tag management, AI, and emerging technologies
• Promote a culture of continuous learning, innovation, and operational excellence
• Identify opportunities to standardize processes and build reusable assets
Good to have
Required Qualifications
• 8+ years of experience in Digital Analytics, Tag Management, Marketing Technology, or Data & Analytics
• Strong hands-on experience with Google Tag Manager (GTM), Tealium, and Google Analytics 4 (GA4)
• Experience with Adobe Analytics, Customer Data Platforms (CDPs), and marketing technology ecosystems
• Strong understanding of digital measurement frameworks, KPI development, and reporting strategies
• Experience in client-facing consulting and stakeholder management
• Strong knowledge of JavaScript, HTML, CSS, browser technologies, and debugging techniques
• Experience with data validation, SQL, and analytics data models
• Proven experience leading analytics implementations from requirement gathering through deployment
• Strong problem-solving and solution design capabilities
Nice to Have:
• Experience with Tealium EventStream, AudienceStream, or server-side tagging
• Experience with cloud platforms such as AWS, Azure, or GCP
• Knowledge of Snowflake, BigQuery, or other modern data platforms
• Experience with Python for automation and analytics use cases
• Familiarity with machine learning and Generative AI technologies
• Experience building AI-powered assistants, analytics copilots, or automation frameworks
• Relevant certifications in Analytics, Cloud, AI, or Tag Management platforms