Labcorp - Manager - Data & Analytics Services

Role : Manager, Data & AI Engineering Play a key role in shaping the future of patient care! Are you interested in making an impact on the quality of human health? Would you like to discover your true potential and expand your knowledgebase as you gain international exposure? If you are looking to work for a large global organization and explore a multitude of career paths, then LabCorp is the place for you! Job Overview : Labcorp is seeking a Manager, Data & AI Engineering resource to join our team at Bengaluru, India Office - (Hybrid). As the Data & AI Engineering Manager at LabCorp, you will lead the development of the LabCorps data platform, analytics capabilities, and AI-driven solutions. This role combines strong expertise in data engineering, reporting enablement, and AI project delivery. As a manager you will oversee a team responsible for building scalable data pipelines, enabling enterprise reporting, and supporting the deployment of AI and machine learning solutions that drive business value. Work Schedule : Candidates are required to follow the work schedule from 10.00 AM to 7.00 PM IST. Key Responsibilities : - Lead and mentor a team of data engineers and AI engineers. - Design and manage scalable data pipelines, data models, and enterprise data platforms. - Develop ready analytics datasets to support business reporting and dashboards using BI tools. - Ensure data quality, governance, reliability, and performance across the data ecosystem. - Manage delivery of AI and machine learning initiatives, working closely with data scientists and business teams. - Oversee the lifecycle of AI/GenAI use cases, from concept to deployment and value realization. - Collaborate with stakeholders to translate business needs into data and AI solutions. - Contribute to the data and AI technology roadmap and architecture strategy. Must-Have Skills : - 10+ years of experience in data engineering, AI engineering, or data platform development. - Proven leadership experience managing data engineering teams. - Strong expertise in ETL/ELT pipelines, SQL, data modeling, and modern data platforms (e.g., Databricks, Snowflake). - Experience enabling BI and reporting solutions (e.g., Tableau, Power BI). - Exposure to AI/ML or GenAI projects, with understanding of model deployment and lifecycle management. - Experience working with cloud platforms (AWS, Azure, or GCP). Qualifications : Bachelors or Masters degree in Computer Science, Engineering, Data Science, or related field.