About this role
Data Engineering Lead Role Summary The Data Engineering Lead is responsible for designing, building, and governing scalable data platforms, pipelines, and analytics solutions that enable business intelligence, advanced analytics, AI/ML, and data-driven decision-making. This role provides technical leadership for data engineering teams, drives architecture standards, and ensures the delivery of high-quality, reliable, and secure data solutions. Key Responsibilities Data Architecture & Engineering Lead the design and implementation of scalable data platforms, data lakes, and cloud-native data solutions.
Architect and optimize data pipelines for ingestion, transformation, validation, and consumption. Define and enforce data modeling standards, including dimensional, operational, and analytical models. Ensure high availability, performance, scalability, and reliability of enterprise data ecosystems.
Technical Leadership Serve as the technical authority for data engineering best practices, standards, and architecture decisions. Lead architecture reviews and provide guidance on complex technical challenges. Mentor and coach senior engineers and developers on modern data engineering practices.
Establish reusable frameworks, patterns, and accelerators to improve delivery efficiency. Cloud Data Platform Management Build and manage enterprise data solutions using Snowflake, Databricks, Azure platforms. Optimize database performance, workload management, storage strategies, and cost governance.
Implement automation for deployment, monitoring, and operational support. Drive adoption of modern ELT/ETL frameworks and DataOps practices. Data Quality, Governance & Security Define and implement data quality frameworks, validation processes, and monitoring solutions.
Ensure compliance with enterprise security, privacy, and regulatory requirements. Partner with governance and business teams to establish metadata, lineage, and stewardship processes. Drive data observability and operational excellence initiatives.
Stakeholder Management Collaborate with Product Owners, Architects, Business Analysts, Data Scientists, and Engineering teams. Translate business requirements into scalable technical solutions. Communicate technical trade-offs, risks, and recommendations to leadership and stakeholders.
Align data platform capabilities with strategic business objectives. Innovation & Strategy Evaluate emerging technologies, AI-enabled data engineering capabilities, and industry best practices. Develop long-term roadmaps for data modernization and platform evolution.
Drive adoption of automation, AI-assisted development, and advanced analytics capabilities. Required Qualifications Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field. 10+ years of experience in Data Engineering with 3+ years in technical leadership roles.
Strong experience with: Snowflake, Databricks, Azure platforms SQL and data modeling Python, Data warehouse and lakehouse architectures CI/CD and DevOps practices API integration and data services Experience leading globally distributed engineering teams. Preferred Qualifications Knowledge of DataOps, MLOps, data governance, and metadata management. Experience in healthcare, life sciences, pharmaceutical, or commercial analytics domains.
Success Metrics Data platform reliability and SLA attainment. Delivery of scalable and cost-efficient data solutions. Reduction in data quality issues and operational incidents.
Engineering productivity improvements through automation. Successful mentoring and development of engineering talent. IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries.
We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete.
Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.