Lead Data Platform Engineer – Data Lakes & Analytics

BioSpace; Indiana; On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Healthcare options

Retirement savings

Paid time off

Job summary

The Digital product engineering team at USP is seeking a Data Engineer to build robust data pipelines, manage large-scale data infrastructure, and enable advanced analytics. This role supports patient safety and health outcomes by delivering clean, accessible data for data scientists, analysts, and business stakeholders.

The ideal candidate will have deep experience in data architecture, cloud technologies, and scalable engineering solutions that drive innovation.

Qualifications

• 7+ years of experience in big data technologies including Python, PySpark and SQL.

Responsibilities

• Design scalable data collection, storage, and processing pipelines to support enterprise-wide data needs.
• Implement data governance frameworks and data quality checks for reliability and compliance.
• Build and optimize data models and data marts to support self-service analytics with Tableau/Power BI/Looker.
• Collaborate with data scientists to operationalize models in production-grade pipelines.
• Partner with business, analytics and engineering teams to translate requirements into scalable data solutions.
• Provide technical leadership and architectural guidance for data platform design.

Skills

Big data analytics

Data governance

Data architecture

Stakeholder communication

Cloud thinking

Education

Bachelor’s degree in Computer Science or related field

Tools

Python

PySpark

SQL

AWS (Redshift, S3, Glue, Lambda, EventBridge)

Airflow

Tableau/Power BI/Looker

Great Expectations

Neo4j

Kappa/Delta Lake

Job description

The Digital product engineering team at USP is seeking a Data Engineer to build robust data pipelines, manage large-scale data infrastructure, and enable advanced analytics. This role supports patient safety and health outcomes by delivering clean, accessible data for data scientists, analysts, and business stakeholders.

The ideal candidate will have deep experience in data architecture, cloud technologies, and scalable engineering solutions that drive innovation.