Associate Director, Data Cloud Engineering

Key Responsibilities

Lead Cloud Data Engineering Strategy

• Design and deliver scalable cloud-native data architectures that support analytics, reporting, activation, and AI-driven use cases.

• Own the integration and optimization of GA4, BigQuery, GCP, and enterprise data platforms.

• Establish best practices for data engineering, cloud architecture, governance, and operational excellence.

• Drive modernization initiatives that enhance scalability, reliability, and performance.

Build and Maintain Analytics Platforms

• Architect and develop robust ETL/ELT pipelines and data workflows.

• Design and optimize enterprise-scale datasets and data models within BigQuery.

• Enable seamless integration between digital data sources, marketing platforms, and enterprise data ecosystems.

• Ensure data is reliable, accessible, and actionable for business users and analytics teams.

Software Engineering & Development

• Contribute to the development of both front-end and back-end solutions supporting analytics products and data applications.

• Develop APIs, microservices, and cloud-native applications that facilitate data access and consumption.

• Apply software engineering best practices, including code quality, testing, CI/CD, version control, and automation.

• Support development of self-service data and reporting capabilities across the organization.

Business Partnership & Stakeholder Engagement

• Partner with senior stakeholders to understand strategic objectives and translate business needs into scalable technical solutions.

• Communicate complex technical concepts to both technical and non-technical audiences.

• Demonstrate the business value of analytics and cloud technologies through measurable outcomes and data-driven storytelling.

• Influence technology decisions through expertise and strategic recommendations.

Innovation, AI & Automation

• Explore and implement emerging cloud, data, and AI technologies to improve business performance.

• Leverage automation and AI-enabled tools to enhance engineering efficiency, data quality, and decision-making.

• Promote responsible AI practices, ensuring appropriate governance, compliance, privacy, and security controls.

Qualifications

• 8+ years of experience in Data Engineering, Analytics Engineering, Cloud Engineering, Software Engineering, or a related field.
• Strong hands-on experience with Google Cloud Platform (GCP) and BigQuery.
• Proven experience designing and building scalable cloud-native data architectures and data pipelines.
• Expertise in SQL and at least one programming language such as Python, JavaScript, or TypeScript.
• Experience developing APIs, integrations, and data services. • Strong understanding of data modeling, data warehousing, ETL/ELT frameworks, and data governance.
• Experience working with enterprise data platforms, data lakes, and analytical ecosystems.
• Ability to partner with business and technical stakeholders to translate requirements into scalable solutions. Desirable Experience
• Experience with Google Analytics 4 (GA4) and digital analytics data structures.
• Understanding of web analytics implementation and measurement frameworks.
• Experience with Google Tag Manager (GTM) and event-based tracking models.
• Exposure to marketing technology (MarTech), customer analytics, or digital marketing measurement.
• Experience with AWS and/or Azure.
• Experience with Looker, Power BI, Tableau, dbt, Airflow, or similar platforms.
• Experience leveraging AI and automation technologies within cloud data environments.
• Experience in pharmaceutical, healthcare, biotechnology, or consumer goods industries.

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.