Senior Data Platform Engineer (Python)

Company: Forte
Location: Chicago, Illinois, United States
Type: Full-time
Posted: 17.FEB.2021


Are you passionate about moving the needle on cancer therapies by combining clinical and molecular datasets? Recent advancements in underly...


Are you passionate about moving the needle on cancer therapies by combining clinical and molecular datasets?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Our client's proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

Great software doesn't happen on its own. It takes great people. That just happens to be our forte. With nearly 20 years of matching top engineering talent with preeminent and innovative brands, we look for inquisitive, resourceful, and dedicated to their craft, and driven to help companies build great software. If this sounds like you, read on.

The Data Platform team is responsible for managing our data infrastructure, architecting and implementing business-critical data pipelines, enabling data driven decision making by building data products, maintaining high code quality standards to improve the availability, reliability and accuracy of our data, and supporting all internal teams. As a Data Platform Engineer, you will architect and implement cloud-native data pipelines and infrastructure to enable analytics and machine learning on the firm's rich clinical, molecular, and imaging datasets.

Core Technologies: AWS Redshift, Py.Spark, Dask, Airflow, and AWS Batch

Why we're looking for you:
• You know what it takes to build and run resilient data pipelines in production and have experience implementing ETL/ELT to load a multi-terabyte enterprise data warehouse.
• Experience building cloud-native data pipelines and applications and supporting technologies/patterns/practices including: AWS, Docker, CI/CD, DevOps, and microservices
• You have implemented analytics applications using multiple database technologies, such as relational, multidimensional (OLAP), key-value, document, or graph
• You value the importance of defining data contracts, and have experience writing specifications including REST APIs
• You write code to transform data between data models and formats, preferably in Python or PySpark
• You've worked in agile environments and are comfortable iterating quickly

Bonus points for:
• Experience moving trained machine learning models into production data pipelines.
• Expert knowledge of relational database modeling concepts, SQL skills, proficiency in query performance tuning, and desire to share knowledge with others.
• Experience or interest in learning Google Cloud Platform Composer, DataProc, BigQuery, GKE

If you feel you could make an impact on this mission, please apply with your resume.

- provided by Dice

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