
Data Warehousing Expert
1 week ago
As a Data Warehouse Architect/Consultant, you will play a pivotal role in designing and implementing enterprise data management strategies that align with business processes.
- Data Management Strategy: Develop and maintain data management frameworks to ensure data quality, consistency, and compliance for various domains such as multi-omics, in-vivo, ex-vivo, and in-vitro datasets.
- Cloud-Based Solutions: Design and develop scalable cloud-based solutions using AWS or Azure following enterprise standards.
- ETL Pipelines: Design and implement complex ETL pipelines to handle semi-structured and structured datasets from labs and scientific platforms.
- Labs Integration: Collaborate with LAB ecosystems (ELNs, LIMS, CDS) to build integration and data solutions around them.
- Stakeholder Collaboration: Work with various stakeholders including data scientists, researchers, and IT teams to optimize data utilization and align data strategies with organizational goals.
What You Bring
- Minimum 7+ years of experience in developing data management solutions solving problems in Discovery/Research domains.
- Advanced knowledge of data management tools and frameworks, including SQL/NoSQL, ETL/ELT tools, and data visualization tools across various private clouds.
- Experience in cloud-based DBMS/data warehouse offerings, ETL tools, and well-versed in different cloud computing offerings in AWS and Azure.
- Hands-on experience with data platforms technologies like Databricks, AWS, Snowflake, and HPC.
- Strong programming skills in languages such as Python and R.
Preferred Qualifications
- MLOps expertise leveraging ML Platforms like Dataiku, Databricks, and Sagemaker.
- Experience with other technologies like Data Sharing (e.g. Starburst), Data Virtualization (Denodo), and API Management (mulesoft).
- Cloud Solution Architect certification (e.g. AWS SA Professional or others).
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