Job description
- Design & Implement an enterprise data management strategy aligned with business process, focusing on data models 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 model for semi-structured/structured datasets by following various modelling techniques
- Design & implement of 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 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 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 b/w 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 (eg. Starburst), Data Virtualization (Denodo), API Management (mulesoft etc)
- Cloud Solution Architect certification (like AWS SA Professional or others)
Role: Data warehouse Architect / Consultant
Industry Type: Management Consulting
Department: Engineering - Software & QA
Employment Type: Full Time, Permanent
Role Category: DBA / Data warehousing
Education
UG: Any Graduate
PG: Any Postgraduate
Key Skills
Cloud computingData analysisData managementdata securityFinancial planningdata visualizationManagementVirtualizationSQLPython