Job Description

About McKesson Compile

Established in 1833, McKesson is a US Fortune 10 global leader in healthcare supply chain management solutions, retail pharmacy, healthcare technology, community oncology, and specialty care. We partner with life sciences companies, manufacturers, providers, pharmacies, governments, and other healthcare organizations to help provide the right medicines, medical products, and healthcare services to the right patients at the right time, safely and cost effectively.


Based in Bangalore India, McKesson Compile's data is a comprehensive, full linked system of record for the US Healthcare market, with intelligence on 2M+ healthcare professionals (HCPs) and over 800K facilities. Compile's data includes high capture medical and pharmacy claims, closed capture Medicare claims (100%), along with best-in-class provider affiliations and customer master.


At McKesson we deliver careers with purpose and potential. Our focus on better health starts with creating an inclusive environment with strong values where you can build a fulfilling career. You can count on us to provide you with resources and opportunities to grow and be your best, while contributing to our pursuit of improving lives.

About Us

At

Compile (a McKesson company)

, we're transforming fragmented healthcare data into powerful intelligence that drives real-world impact -- from mapping patient journeys to optimizing go-to-market strategies for life sciences.


We're building a modern, scalable, and secure

data platform

that powers data products across the organization. As a

Principal Engineer

, you'll be the hands-on technical leader driving the design and development of this foundational platform.


If you're passionate about clean architecture, distributed systems, and solving real-world data challenges -- especially in healthcare -- this is your opportunity to make a deep impact.

What You'll Do

Architect and lead development of a

reusable, scalable data platform framework

Design robust

ETL/ELT pipelines

for structured and semi-structured healthcare data Build APIs and internal tools using

Django

, focused on performance and maintainability Use

Prefect

for orchestration, and

Ray

or

Spark

for distributed compute Leverage

Databricks

for testing and validation of data pipelines (not for primary compute) Enforce

data quality, observability

, and reliability using

Metaplane

or similar tools Integrate and manage data across

Postgres, Snowflake

, and

Snowflake Shares

Optimize for scalability and performance in a

cloud-native Azure

environment Mentor engineers and collaborate with product, data, and platform teams

Tech Stack

Languages & Frameworks:

Python (Django, FastAPI), SQL

Orchestration & Compute:

Prefect, Ray, Apache Spark

Data Storage:

Postgres, Snowflake, dbt, Snowflake Shares

Cloud Platform:

Azure (Blob Storage, Data Factory, Azure Functions)

Testing & CI/CD:

Pytest, GitHub Actions, Databricks (for test pipelines)

Observability:

Metaplane or similar data observability tooling

Nice-to-Have:

Apache Iceberg, Airbyte, familiarity with GenAI/LLM concepts (e.g., RAG, embeddings, vector stores)

What We're Looking For

15+ years

of experience in

data engineering, platform architecture

, or backend systems Proven experience designing and building

modular data infrastructure

Hands-on expertise with

ETL frameworks, orchestration tools (Prefect), and distributed compute (Ray/Spark)

Strong experience in

Django-based API development

Deep understanding of

data modeling, warehousing

, and

pipeline reliability

Experience with

Azure cloud services

and managing large datasets across

Snowflake and Postgres

Familiarity with

data observability and monitoring

tools (e.g., Metaplane) Nice-to-have: Exposure to

GenAI/LLM systems

such as vector search or RAG pipelines Experience with

healthcare or life sciences data

is a strong plus

Work Environment

Location:

Bangalore (Hybrid - 3 days/week in office) High-ownership, collaborative engineering culture Lean, fast-moving team solving tough technical and domain problems * Backed by

McKesson

, one of the world's largest healthcare companies