Manage a portfolio of customer delivery projects by collaborating with a joint team of our clients and Rhino Product, Engineering, and Sales.
Design and implement custom production grade data pipelines, code ETL workflows, and perform data validation and data quality checks, and advise on system performance optimization, integrating with source databases, and Rhino API/SDK/UI.
Onboard and educate users and equip the users with training and tutorials and demonstrate deep technical understanding of the product.
Provide project management support to help users achieve successful Rhino FCP implementations.
Advise customers on the use of the Rhino Federated Computing Platform, containerization technology, data harmonization, database integrations, data cataloging, and security and data governance configurations.
Create tutorials and cookbooks related to data transformation and data annotation workflows.
Help debug technical issues with users and implement effective support process improvements.
Advise the Product organization on features that would help advance use of the platform understanding the use cases required of customers.

Competencies

In order to perform the set of responsibilities above, we should probe for examples of the specific skills listed below:

Must-Have:

Hands-on building experience with batch and streaming data ingestion (example- Kafka) , data replication (example -Fivertran, Oracle Goldengate etc.), data warehousing (BigQuery, Redshift, Snowflake, Databricks), distributed storage systems (S3, GCS), data modeling (OMOP/FHIR or other industry common data models), data security (example - Identity and access management systems, key management systems), and data transformations(Python, SQL,DBT, Spark), data quality, and data observability.
Proficiency in Python and SQL coding - in developing ETL workflows.
4+ years of data engineering experience.

Preferred :

Healthcare, Biopharma, Financial Services, Public Sector industry experience.
Healthcare or Biology Data Modeling and Clinical Informatics or Bioinformatics
Data Science Life Cycle experience.
Experience with data workflow automation tools (example- airflow), containerization tools (Docker or similar), and CI/CD tools.
Experience with pre-sales, post-sales in a data platform product company.
Degree in a quantitative field, with computer science or engineering or biomedical informatics/bioinformatics preferred.

Additional Info:

This job is no longer accepting applications