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LabCorp

Global life sciences R&D services

Manager, Data & Analytics Services

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree in computer science, engineering, information systems, or a related field.
  • At least 8 years of experience in data engineering, data warehousing, and analytics solutions.
  • At least 5 years of hands-on experience with PySpark, Python, Spark, SQL, and scalable data processing frameworks.
  • At least 5 years of Snowflake and/or Databricks implementation experience.
  • At least 3 years of experience handling structured, semi-structured, and unstructured data formats, including XML, JSON, Avro, and Parquet.
  • At least 4 years of experience designing and implementing ETL/ELT solutions from multiple enterprise data sources.
  • At least 4 years of experience developing modern cloud-native data platforms and data pipelines.
  • At least 4 years of experience supporting enterprise reporting and analytics solutions using Power BI, Tableau, or similar reporting platforms.
  • At least 4 years of experience working with AI-assisted development tools and applying AI capabilities to improve software delivery, testing, documentation, and development productivity.
  • 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.
  • 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.

Responsibilities

  • Mentor junior engineers and promote engineering best practices across the team.
  • 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.
  • Collaborate with business stakeholders, analysts, and development teams to gather requirements and translate them into scalable data solutions.
  • 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.
  • Analyze 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 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 standards.
  • Stay current with emerging technologies and industry trends to inform innovation and continuous improvement efforts.

Desired Qualifications

  • Experience in the healthcare, diagnostics, life sciences, or pharmaceutical industry is a plus.

About the Company

LabCorp

Global life sciences R&D services

Labcorp provides global life sciences and healthcare R&D services, supporting pharma, biotech, and crop protection clients with testing, safety assessments, and regulatory submissions. It conducts studies ranging from basic physicochemical tests to complex inhalation toxicology and uses specialized facilities to evaluate inhaled substances and ensure regulatory compliance. Its global presence and integrated suite of services enable clients to move projects from early development to product approval within one organization. Labcorp aims to help clients bring safe, effective products to market efficiently, advancing human health and scientific research.

Company size
10,001+
Company stage
IPO
Headquarters
Burlington, VT
Founded
1976

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