Analytics Engineer

Who Are We?

Prolaio believes that continuous learning and collaboration can make a significant difference in how heart care is administered. We are creating smarter ways to address heart disease and heart risks by integrating a connected platform enabled by smart data science to help patients access the care and attention that will inform better treatments and outcomes.

We envision a future where care teams and hospitals can be more effective, the healthcare system can be more efficient, and patients have a better care experience and more fulfilling lives.

This is precision cardiology, and we know it’s within reach.

What Will You Do?

The Overview

The Analytics Engineer will be a foundational member of the Data Services team, responsible for building scalable data pipelines, frameworks, and tools to automate the clinical trial data products, with an emphasis on data quality verification. The Analytics Engineer will work closely with cross-functional teams to ensure data quality, reliability, and readiness for client delivery.

The Specifics

• Design, build, and maintain data pipelines using Python, SQL, BigQuery and DBT.
• Develop frameworks and internal tools to automate data mapping, transformation, and quality verification.
• Implement and monitor data quality checks to ensure reliable and accurate datasets for downstream analysis.
• Collaborate with Data Services leadership to standardize data workflows and enable scalability across multiple clinical projects.
• Document pipelines, processes, and frameworks to ensure reproducibility and ease of adoption for future hires.
• Partner with Data Engineering to align on data needs and delivery timelines.
• Support client-facing data discussions, providing technical expertise as needed.

Why Prolaio?

• Impactful Work: You will join in the fight against heart failure (HF) and hypertrophic cardiomyopathy (HCM) with the goal of extending and saving the lives of our patients while also being at the forefront of changing the healthcare industry through technology.
• Innovative Environment: You will be part of an organization doing something that’s never been done before.
• Professional Growth: You will join a growing team and have a substantial impact on our daily and future operations with the opportunity to continuously learn and grow.
• Collaborative Team: You will be part of a team of collaborative, curious, and committed individuals focused on the collective good, inclusiveness, scientific excellence, and advancing digital health for cardiology.

Who You Are?

• BS/MS in Computer Science, Mathematics, Engineering or related STEM fields.
• 3-5 years of experience in designing, developing, deploying, and maintaining robust data pipelines and data warehouse solutions.
• Proficiency in Python, SQL, and data modeling, ideally with BigQuery or other cloud data warehouses.
• Proven track record in designing scalable, automated workflows for data processing and quality verification.
• Hands-on experience with dbt or equivalent data transformation frameworks.
• Strong problem-solving skills, attention to detail, and ability to thrive in an early-stage team environment.

Additional Qualifications (Nice to Haves)

• Exposure to clinical trial, healthcare, or life sciences data (training can be provided).
• Familiarity with orchestration tools (e.g., Airflow, Metaflow) and modern data stack best practices.
• Strong communication skills and willingness to engage in cross-functional and client-facing discussions.
• Ambition to take on leadership responsibilities as the Data Services team grows.
• Experience in customer-facing roles is a plus.
• Experience in time series analyses and/or signal processing a plus.

Company Benefits

• Competitive Compensation: Competitive salary plus performance bonus and equity.
• Health Benefits: Medical, dental, and vision benefits with generous company contribution.
• Life Insurance: Company-provided life insurance.
• Retirement Plan: 401(k) plan.
• Paid Time Off: 13 paid company holidays, 15 vacation days and 5 sick days.
• Parental Leave: Paid parental leave.