Labcorp is a global leader in laboratory services, providing the insights and answers that help healthcare providers, patients, researchers, pharmaceutical companies and health systems make confident decisions and improve outcomes. Through our unparalleled science, data, technology and laboratory network, we advance diagnostics, accelerate innovation and help address some of the world’s most important health challenges. As we shape the future of healthcare, we are leveraging advanced technologies, intelligent digital solutions and data-driven innovation across our operations to enhance how work gets done and deliver greater value to customers and patients. With our global scale and deep expertise, you’ll have the opportunity to do meaningful work, grow your career and make a real impact on people’s health around the world. Together, we’re improving health and improving lives.
Labcorp is a global leader in diagnostic testing and drug development solutions, helping healthcare providers, researchers, and patients make informed decisions that advance care. Join us in our mission to improve health and improve lives.
Labcorp is seeking a Manager, Data & Analytics Services to join our team at Bengaluru, India Office.
Work Schedule: This is a full‑time, exempt (salaried) position assigned to a Second Shift schedule, with standard business hours of Monday through Friday, 11:00 a.m. to 8.00 p.m.in your local time zone. Business needs may occasionally require flexibility in work hours, including earlier, later, or additional hours, with reasonable notice provided when possible.
Job Responsibilities
Team Development and Mentorship
- Mentor junior engineers and promote engineering best practices across the team.
Technical Oversight
- Design and implement highly performant data ingestion and transformation pipelines from multiple enterprise data sources.
- Develop scalable, reusable, and maintainable data engineering frameworks to support analytics, reporting, and operational workloads.
- Integrate end-to-end data pipelines from source systems to target repositories while ensuring data quality, consistency, security, and governance.
- Design and support modern cloud-based data platforms using Snowflake, Databricks, AWS, and related technologies.
- Work with event-based and streaming technologies to ingest and process real-time data.
Collaboration and Stakeholder Management
- Collaborate with business stakeholders, analysts, and development teams to gather requirements and translate them into scalable data solutions.
Delivery and Operations
- Design and implement curated datasets and semantic layers that support self-service analytics and enterprise reporting.
- Support the development and delivery of executive dashboards, operational reporting, and business intelligence solutions using Power BI, Tableau, or similar platforms.
- Perform analysis of new business requirements and recommend optimal technical solutions and architecture patterns.
- Deliver and present proof of concepts for key technology components and data platform capabilities to project stakeholders.
- Evaluate emerging technologies, platforms, and tools against business and technical requirements.
- Leverage AI-powered development tools and practices to improve engineering productivity, code quality, testing, documentation, and solution delivery.
- Apply AI-Driven Development Lifecycle (AI-DLC) practices across design, development, testing, deployment, and operational support activities.
- Participate in code reviews, architecture discussions, and continuous improvement initiatives to enhance delivery effectiveness and engineering standard
Innovation and Emerging Technologies
- Stay current with emerging technologies and industry trends to inform innovation and continuous improvement efforts.
Minimum Qualifications
- Bachelor’s degree in computer science, Engineering, Information Systems, or a related field.
- 8 or more years of experience in Data Engineering, Data Warehousing, and Analytics solutions.
- 5 or more years of hands-on experience with PySpark, Python, Spark, SQL, and scalable data processing frameworks.
- 5 or more years of Snowflake and/or Databricks implementation experience.
- 3 or more years of strong experience handling structured, semi-structured, and unstructured data formats including XML, JSON, Avro, and Parquet.
- 4 or more years of experience designing and implementing ETL/ELT solutions from multiple enterprise data sources.
- 4 or more years of experience developing modern cloud-native data platforms and data pipelines.
- 4 or more years of experience supporting enterprise reporting and analytics solutions using Power BI, Tableau, or similar reporting platforms.
- 4 or more years of experience working with AI-assisted development tools and applying AI capabilities to improve software delivery, testing, documentation, and development productivity.
Additional Job Standards
- Strong experience with modern orchestration and scheduling tools such as Airflow, Matillion, or similar platforms.
- Strong understanding of data quality, data governance, and data lifecycle management principles.
- Experience in CI/CD practices using Jenkins, Terraform, Docker, GitHub, AWS, and Kubernetes.
- Experience working with distributed data processing technologies including Hadoop, Spark, Kafka, and streaming frameworks.
- Strong experience in business intelligence, reporting, analytics, and data visualization solutions.
- Good working knowledge of AWS technologies including EC2, S3, Lambda, SQS, SNS, and related cloud services.
- Strong programming experience using SQL, PL/SQL, stored procedures, views, materialized views, indexing, and database optimization techniques.
- Strong understanding of Data Warehousing concepts, including Fact and Dimension modeling, Star Schemas, Snowflake Schemas, and data integration patterns.
- Excellent communication, stakeholder management, and collaboration skills.
- Ability to lead technical discussions, solution design workshops, and architecture reviews.
- Demonstrated ability to leverage AI-powered engineering tools to improve delivery quality, accelerate development cycles, and support continuous innovation.
- Experience in Healthcare, Diagnostics, Life Sciences, or Pharma industry is a plus.
About the Role
We are seeking a highly skilled Manager, Data & Analytics Services with 8 plus years of experience to Design and implement highly performant data ingestion and transformation pipelines from multiple enterprise data sources. The ideal candidate will have strong expertise in Data Engineering, Data Warehousing and Analytics solutions experience and strong experience with PySpark, Python, Spark, SQL, and scalable data processing frameworks along with the experience into Snowflake and/or Databricks implementation experience and implementing ETL/ELT solutions from multiple enterprise data sources. and best practices, and will collaborate closely with business stakeholders, analysts, and development teams to gather requirements and translate them into scalable data solutions.
Labcorp is proud to be an Equal Opportunity Employer:
Labcorp strives for inclusion and belonging in the workforce and does not tolerate harassment or discrimination of any kind. We make employment decisions based on the needs of our business and the qualifications and merit of the individual. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), family or parental status, marital, civil union or domestic partnership status, sexual orientation, gender identity, gender expression, personal appearance, age, veteran status, disability, genetic information, or any other legally protected characteristic. Additionally, all qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law.
We encourage all to apply
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Skills Required
- Bachelor's degree in computer science, engineering, information systems, or a related field
- 8 or more years of experience in data engineering, data warehousing, and analytics solutions
- 5 or more years of hands-on experience with PySpark, Python, Spark, SQL, and scalable data processing frameworks
- 5 or more years of Snowflake and/or Databricks implementation experience
- 3 or more years handling structured, semi-structured, and unstructured data formats, including XML, JSON, Avro, and Parquet
- 4 or more years designing and implementing ETL/ELT solutions from multiple enterprise data sources
- 4 or more years developing modern cloud-native data platforms and data pipelines
- 4 or more years supporting enterprise reporting and analytics solutions using Power BI, Tableau, or similar platforms
- 4 or more years working with AI-assisted development tools and applying AI capabilities to software delivery, testing, documentation, and productivity
- Experience with orchestration and scheduling tools such as Airflow or Matillion
- Understanding of data quality, data governance, and data lifecycle management principles
- Experience with CI/CD using Jenkins, Terraform, Docker, GitHub, AWS, and Kubernetes
- Experience with distributed data processing technologies including Hadoop, Spark, Kafka, and streaming frameworks
- Strong programming experience with SQL, PL/SQL, stored procedures, views, materialized views, indexing, and database optimization
- Understanding of data warehousing concepts, fact and dimension modeling, star schemas, snowflake schemas, and data integration patterns
- Excellent communication, stakeholder management, and collaboration skills
- Ability to lead technical discussions, solution design workshops, and architecture reviews
- Experience in healthcare, diagnostics, life sciences, or pharmaceutical industries
What We Do
We believe in harnessing science for human good. And so we work day and night, around the world, to deliver answers for all your health questions—whether you’re a provider, drug developer, hospital, medical researcher or patient. That means everything from advancing diagnostic testing to helping launch new drugs, to offering new perspectives through data - all drawing from a deep well of scientific expertise. So when you need trusted information to make clear, confident health decisions, consider us your source.





