Global Data & AI Product Engineer

PharmaEssentia Corporation; Burlington (MA); Hybrid; USD 116,000 - 150,000; Full time

Benefits offered by this job

Comprehensive medical coverage

401(k) retirement plan with company-m

Generous paid time off

Cell phone reimbursement

Job summary

PharmaEssentia USA is seeking a hands-on Data Product Engineer to transform raw data into curated, reusable data tables that support analytics and AI applications. You will integrate pharma data sources, codify business rules, and develop production data products with a focus on reliability and maintainability.

You will partner with cross-functional teams to design, deploy, monitor, and enhance data products, reducing manual data work and accelerating decision-making while ensuring data quality

Qualifications

• Strong SQL and hands-on Python skills for data transformation, automation, testing, and optimization.
• Experience with Snowflake or a comparable cloud data warehouse and ELT patterns; dbt preferred.
• Excellent communication and collaboration with technical teams, business stakeholders, and external data vendors.

Responsibilities

• Design, build, test, deploy, and maintain data transformations and production-ready datasets in Snowflake.
• Build integrated data products from multiple data sources (claims, CRM, HCP/HCO hierarchies, distributors, payers).
• Translate requirements into scalable technical designs and data products under supervision.
• Implement tests, data-quality controls, and alerts; monitor and resolve production issues.

Skills

SQL

Python

Communication

Ownership

Education

Bachelor’s or Master’s degree in CS/Data/Engineering

Tools

Snowflake

dbt

Job description

PharmaEssentia USA is seeking a hands-on Data Product Engineer to transform raw data into curated, reusable data tables that support analytics and AI applications. You will integrate pharma data sources, codify business rules, and develop production data products with a focus on reliability and maintainability.

You will partner with cross-functional teams to design, deploy, monitor, and enhance data products, reducing manual data work and accelerating decision-making while ensuring data quality