Job Summary
Sr Developer role in an MNC focusing on SAP Datasphere solutions within Cheminformatics and Bioinformatics domains. The professional will design and optimize data models dataflows and replication flows to support scientific analytics in a hybrid work model. The role involves close collaboration with cross functional teams to deliver reliable and secure enterprise data products.
Responsibilities
- Design and implement robust SAP Datasphere replication flows that ensure accurate and timely synchronization of scientific and enterprise data across multiple source systems and target layers
- Develop and optimize SAP Datasphere dataflows that efficiently transform raw laboratory and research data into curated datasets ready for downstream analytics and reporting
- Build scalable SAP Datasphere data models that support complex Cheminformatics and Bioinformatics use cases while maintaining performance consistency and traceability
- Configure and refine data pipelines that integrate experimental results chemical structures biological sequences and external reference data into unified domain specific data assets
- Collaborate with domain experts in Cheminformatics and Bioinformatics to translate scientific requirements into technical data models and transformation logic aligned with best practices
- Analyze existing data integration solutions to identify performance bottlenecks and implement enhancements that reduce processing time and improve reliability
- Implement rigorous data validation and quality checks within SAP Datasphere flows to ensure that scientific and operational stakeholders can trust the accuracy of delivered data
- Coordinate with analytics and application teams to provide well structured data marts and views that enable advanced modelling dashboards and scientific decision support tools
- Document data architectures data lineage and transformation logic in a clear reusable manner to support maintainability knowledge sharing and onboarding of new team members
- Apply secure data handling practices to protect sensitive research data and regulatory relevant information while still enabling efficient collaboration across global teams
- Troubleshoot issues in data replication dataflows and models by performing systematic root cause analysis and implementing sustainable corrective actions
- Engage in continuous improvement activities by evaluating new SAP Datasphere features and proposing incremental enhancements that increase automation and reduce manual interventions
- Support hybrid work collaboration by participating in virtual ceremonies and on site workshops to ensure alignment with project timelines quality expectations and stakeholder outcomes
Qualifications
- Possess professional experience in designing SAP Datasphere replication flows with a focus on reliability monitoring and operational readiness for enterprise scale data landscapes
- Demonstrate strong skills in developing SAP Datasphere dataflows including complex transformations joins aggregations and reusable components that support modular designs
- Bring hands on experience in SAP Datasphere data modelling covering relational models semantic layers star schemas and object reuse to support analytical and scientific workloads
- Exhibit practical exposure to Cheminformatics including handling molecular descriptor datasets compound libraries assay results and related metadata within structured data platforms
- Show experience in Bioinformatics data scenarios such as sequence data annotations experimental results integration and mapping to standardized taxonomies within enterprise systems
- Apply sound knowledge of SQL data warehousing concepts and dimensional modelling to design performant and maintainable datasets used by reporting and advanced analytics solutions
- Utilize experience with data quality management profiling and cleansing methods to ensure that scientific and business users receive consistent complete and validated information
- Communicate effectively with cross functional stakeholders such as scientists analysts and product teams to clarify requirements negotiate priorities and manage expectations
- Adapt quickly to new tools and processes within SAP cloud environments while following organizational standards for coding documentation testing and deployment
- Display strong problem solving capabilities by independently analyzing complex data issues proposing options and implementing solutions within agreed timelines and quality thresholds
- Maintain awareness of regulatory and compliance considerations relevant to scientific data and embed these constraints into data design retention and access control strategies
- Contribute to team outcomes by participating in code reviews knowledge sharing sessions and process retrospectives that drive continuous improvement of data development practices
Certifications Required
SAP Certified Application Associate SAP Datasphere or equivalent enterprise data warehousing certification preferred
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
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