Data Curation Engineer

Tellus Solutions is in partnership with a committed biopharmaceutical company in North Chicago focused on providing innovative therapies. Your technical expertise as a Data Curation Engineer in the area of SQL, building and running workflows for RDMS data loading and ETL processes will contribute to our client's innovative therapies which will impact the quality and duration of life.

Job Description:

As a Data Curation Engineer in the Genomics Research Center, you will be responsible for building and running workflows to load and manage high-value datasets in a centralized environment.

You will work closely with Bioinformatics Engineering, as well as bioinformatics research scientists to identify data sources and requirements for loading and querying.

Your expertise in PostgreSQL for database management and Python and R for scripting and automation will be crucial in developing and maintaining ETL processes to ensure data quality and integrity.

Responsibilities:

Develop and implement workflows to load and manage genomic data.

Work with researchers and data scientists to identify data sources and requirements for loading new datasets.

Maintain existing data models for storing and querying genomic data.

Develop and maintain ETL processes to ensure data quality and integrity.

Build and maintain scripts for automation of data loading and processing.

Qualifications:

Bachelor's degree in computer science, bioinformatics, or a related field +3 years of applicable experience.

Experience with building and running workflows for RDMS data loading and ETL processes.

Demonstrated experience building ETL environments from scratch.

Familiarity with AWS ETL services (e.g., Glue, Athena).

Proficient in PostgreSQL (or equivalent) and ability to write complex queries for data extraction and analysis.

Strong programming skills in Python and R for scripting and automation.

Familiarity with genomic data formats and databases commonly used in bioinformatics research.

Knowledge of data modeling concepts and implementing common data models in a relational database.

Familiarity with data cleaning, normalization, and quality control processes.

Excellent communication skills and ability to collaborate with researchers and stakeholders.