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What You'll Do
- Design & implement an enterprise data management strategy aligned with business process, focusing on data model designs, database development standards, and data management frameworks.
- Develop and maintain data management and governance frameworks to ensure data quality, consistency, and compliance for different Discover domains such as Multi omics, In Vivo, Ex Vivo, In Vitro datasets.
- Design and develop scalable cloud-based (AWS or Azure) solutions following enterprise standards.
- Design robust data models for semi-structured/structured datasets by following various modeling techniques.
- Design & implement complex ETL data-pipelines to handle various semi-structured/structured datasets coming from Labs and scientific platforms.
- Work with LAB ecosystems (ELNs, LIMS, CDS etc.) to build integration & data solutions around them.
- Collaborate with various stakeholders, including data scientists, researchers, and IT, to optimize data utilization and align data strategies with organizational goals.
- Stay abreast of the latest trends in Data management technologies and introduce innovative approaches to data analysis and pipeline development.
- Lead projects from conception to completion, ensuring alignment with enterprise goals and standards.
- Communicate complex technical details effectively to both technical and non-technical stakeholders.
What You'll Bring
- Minimum of 7+ years of hands-on experience in developing data management solutions solving problems in the Discovery/Research domain.
- Advanced knowledge of data management tools and frameworks, such as SQL/NoSQL, ETL/ELT tools, and data visualization tools across various private clouds.
- Strong experience in the following:
Cloud-based DBMS/Data warehouse offerings
- AWS Redshift, AWS RDS/Aurora, Snowflake, Databricks.
- ETL tools Cloud-based tools.
- Well versed with different cloud computing offerings in AWS and Azure.
- Well aware of Industry-followed data security and governance norms.
- Building API Integration layers between multiple systems.
- Hands-on experience with data platforms technologies like Databricks, AWS, Snowflake, HPC (certifications will be a plus).
- Strong programming skills in languages such as Python, R.
- Strong organizational and leadership skills.
- Bachelor's or Master's degree in Computational Biology, Computer Science, or a related field. Ph.D. is a plus.
Preferred/Good To Have
- MLOps expertise leveraging ML Platforms like Dataiku, Databricks, Sagemaker.
- Experience with other technologies like Data Sharing (e.g., Starburst), Data Virtualization (Denodo), API Management (Mulesoft etc.).
- Cloud Solution Architect certification (like AWS SA Professional or others).
