Data Platform Engineer
hace 3 semanas
They work with leading health systems, academic medical centers, and community hospitals across the country. They provide the first complete system for transforming healthcare operations: AI / ML-based platform, Best-practice solutions, Expert change management.
They are looking for a Data Engineer II to help build the next generation of their data ecosystem as part of their Data Platform team. The Data Platform team acts as stewards for the client’s data. They manage the data ecosystem from technical infrastructure to data architecture and tactical data transformations to unlock data as strategic asset in powering high quality decision making at scale. Their services support both internal & external decision making from product development and client insights to ultimately supporting the development and operationalization of their Healthcare AI to improve the lives of patients and doctors across the country.
**About the position**:
As a Data Engineer II, you will build and maintain significant components of the client's data architecture for their custom solution. You will be comfortable working closely with both core data users on analytics and data science and backend partners to design, build, and deploy comprehensive data pipelines in support of internal and external data solutions - from data requirement & quality definitions, to pipeline design, to feature engineering within the healthcare space (and HIPAA restrictions). You will be motivated and excited to have an impact on the team and in the company and to improve the quality of healthcare operations.
**Key Responsibilities**: Build, tune, and improve the end-to-end workflow of data users at out client's to data driven decisions & product features (incl. designing data structures, building and scheduling data transformation pipelines, improving access to critical data assets etc.). Improve the overall definition and quality of our data assets incl. the automation and management of schema lifecycles, improved tooling for data flow visibility, and data quality tooling/monitoring Support the optimization and scale of existing pipelines, dashboards, and data science feature engineering to support our client's scale Collaborate with data infrastructure and engineering teams to build, extend, and envision cross-platform ETL and reports generation frameworks to raise engineering standards.
**Key Qualifications**: Demonstrated experience in leading data modeling & transformation pipeline design for production services and data science / analytics partner needs (strong SQL & DBT experience preferred).
**Place of work**: Remote. Anywhere from LatAm
**Contract Type**: Full time - Contractor. Long-term. Paid in USD
**Selection process**: Screening 45' Technical Challenge (2 hours take home) Technical Interview 90'
The client is a world’s leading healthcare operations platform, generating over 15 billion patient predictions per year.
**Requisitos**:
**Tech Skills (required)**: Master’s degree in CS, CE or similar technical discipline Advanced English Level Data Pipelines / Modeling / SQL : 5 years of professional exp. leading data modeling & transformation pipeline design for production services and data science / analytics partner needs. Python : 5 years of professional exp. in connection with data (not traditional backend software developing). Data Visualization : Experience optimizing & designing the data processing for modern data visualization tools (Looker preferred). Analytics : Experience analyzing data to identify deliverables, gaps, and inconsistencies to ultimately refine dataset requirements and standards.
**Nice to have**: Airflow/Snowflake/DBT: Working, hands on, knowledge of modern Data Warehouses & ETL tools (Snowflake, Airflow). Kafka / Spark: Practical hands on experience with data lake / schema discovery systems and relevant technologies. OO/Modern Languages: Professional experience working with modern programming languages (Java, C++, Golang) AWS: Familiarity with the AWS ecosystem (Lambda, RDS, Redshift etc.) Athena: Practical hands on experience with data lake / schema discovery systems and relevant technologies. DynamoDB / Confluent : Practical hands on experience with data lake / schema discovery systems and relevant technologies. Unstructured data processing: Experience handling unstructured data, especially working with NLP tooling to extract information from text.
Beneficios
Paid Vacations (2 weeks) Local Holidays 100% remote Stock options
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