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.
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