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Prolaio is seeking a Data Engineer to join our team in the Chicagoland area with flexibility for remote locations. You will enhance our data platform by building scalable data lakes, developing pipelines, and collaborating with data scientists and product teams.
The role requires 3–5 years of data engineering or ML engineering experience, strong cloud proficiency (GCP/AWS/Azure), and expertise in Python and SQL for data manipulation.
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 uniting patients, care teams, and researchers on a secure, technology-enabled platform that drives clinical innovation and offers a path towards better patient outcomes.
This is precision cardiology, and we know it's within reach.
The Overview
We are seeking a skilled and motivated Data Engineer to join our Data Engineering team. In this role, you will enhance our data platform, developing and optimizing data pipelines that power advanced analytics and machine learning models. You'll work closely with data scientists, product teams, and other engineers to ensure that our data platform supports ongoing innovation. This role will report to the Lead Data Engineer. We would love to find someone in the Chicagoland area who can collaborate with the team in the office, but are also open to the right candidate in another location.
Data Lake Implementation: Develop, manage and operate data lakes on cloud platforms like Google Cloud Platform (GCP), ensuring scalability, reliability, and performance.
Automation and Scripting: Utilize Python or other scripting languages to automate data workflows, improve operational efficiency, and support machine learning models.
Data Pipeline Development: Use Dagster, dbt, and other tools to transform and model raw data into a structured format for analytics and reporting.
Security and Compliance: Work inside a regulated SDLC. Ensure that all data processes adhere to security best practices, especially around PII and PHI, and maintain compliance with relevant regulatory standards.
Collaboration: Work closely with data scientists, product teams, and engineers to align data solutions with business and product needs.
Problem Solving: Tackle complex technical challenges and contribute to continuous improvement initiatives.
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
3-5 years of experience as a Data Engineer, ML Engineer, or similar role.
Cloud Proficiency: Strong experience with Google Cloud Platform (GCP) or other cloud platforms like AWS or Azure.
Data Warehousing: Hands-on experience with BigQuery, or with Databricks, Snowflake, Redshift or a comparable cloud warehouse.
Orchestration: Experience with Dagster, Airflow, Prefect or a comparable orchestrator.
Programming Skills: Proficiency in Python and SQL for data manipulation and automation.
Data Lakes: Experience with implementing and managing data lakes.
Communication Skills: Strong problem-solving, communication, and collaboration abilities.
Starting Salary is at $134,000.00 (Exact Compensation may vary based on skills, experience, and location)