Lead Data Engineer

Job Summary

Job Description

We are seeking a Lead Data Engineer to design and build the data infrastructure that powers our applied AI initiatives. This role is the first data engineering hire for our AI team, making it an exciting opportunity for a builder and innovator who enjoys creating AI-ready data ecosystems from the ground up. The ideal candidate is someone who excels at building scalable data platforms for structured and unstructured data, supports ML and GenAI workflows, and thrives in a collaborative, fast-moving environment.

Responsibilities:

• Data Architecture: Design and implement end-to-end data platforms that support AI/ML pipelines, including batch, real-time, and streaming use cases.
• Data Pipelines: Build, maintain, and optimize data pipelines that support large-scale structured and unstructured data for training and inference.
• ML and GenAI Readiness: Develop data workflows that support traditional machine learning, NLP, and generative AI use cases (e.g., embeddings, feature stores).
• Collaboration: Partner with data scientists, AI engineers, cloud architects, and stakeholders to create efficient and secure data solutions.
• Performance and Automation: Ensure data pipelines and workflows are reliable, efficient, and cost-effective, leveraging CI/CD and infrastructure-as-code principles.
• Data Quality and Security: Implement data quality, governance, and security practices to ensure compliant and trustworthy data across AI systems.
• Leadership and Mentorship: Lead data engineering efforts and provide mentorship as the team grows over time.

Qualifications:

• Experience:
  • At least 5+ years of experience in data engineering, with expertise in building cloud-native data systems (AWS, Azure, or Google Cloud Platform).
  • Experience designing and managing AI/ML pipelines that support model training, feature engineering, and real-time inference.
  • Strong proficiency in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, Snowflake).
• Cloud-Native Proficiency:
  • Deep experience with cloud data storage and processing tools (e.g., S3, BigQuery, Azure Data Lake).
  • Familiarity with containerization (Docker, Kubernetes) and CI/CD frameworks for data workflows.
• Preferred (but not required):
  • Familiarity with vector databases (e.g., Pinecone, Weaviate) and embedding stores.
  • Experience operationalizing generative AI models or working with APIs (e.g., OpenAI, Hugging Face).

Soft Skills:

• Strong communication and collaboration skills to work across cross-functional teams.
• Ability to navigate ambiguity and prioritize building scalable solutions for long-term success.

Education:
Bachelor?s degree in Computer Science, Engineering, or a related field. A Master?s degree is a plus but not required.

Medline Industries, LP, and its subsidiaries, offer a competitive total rewards package, continuing education & training, and tremendous potential with a growing worldwide organization.

The anticipated salary range for this position:

The actual salary will vary based on applicant?s location, education, experience, skills, and abilities. This role is bonus and/or incentive eligible. Medline will not pay less than the applicable minimum wage or salary threshold.

Our benefit package includes health insurance, life and disability, 401(k) contributions, paid time off, etc., for employees working 30 or more hours per week on average. For a more comprehensive list of our benefits please click . For roles where employees work less than 30 hours per week, benefits include 401(k) contributions as well as access to the Employee Assistance Program, Employee Resource Groups and the Employee Service Corp.

Every day, we?re focused on building a more diverse and inclusive company, one that recognizes, values and respects the differences we all bring to the workplace. From doing what?s right to delivering business results, together, we?re better. Explore our Diversity, Equity and Inclusion page .

Medline Industries, LP is an equal opportunity employer. Medline evaluates qualified applicants without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, protected veteran status, disability/handicap status or any other legally protected characteristic.