Job
Description
Job description Architectural Assessment Road mapping Conduct a comprehensive assessment of the current R D Data Lake architecture. Propose and design the architecture for the next-generation self-service R&D Data Lake based on defined product specifications. Contribute to defining a detailed architectural roadmap that incorporates the latest enterprise patterns and strategic recommendations for the engineering team. Data Ingestion & Processing Enhancements Design and prototype updated data ingestion mechanisms that meet GxP validation requirements and improve data flow efficiency. Architect advanced data and metadata processing techniques to enhance data quality and accessibility Storage Patterns OptimizationEvaluate optimized storage patterns to ensure scalability, performance, and cost-effectiveness. Design updated storage solutions aligned with technical roadmap objectives and compliance standards. Data Handling & Governance Define and document standardized data handling procedures that adhere to GxP and data governance policies. Collaborate with governance teams to ensure procedures align with regulatory standards and best practices.Assess current security measures and implement robust access controls to protect sensitive R&D data. Ensure that all security enhancements adhere to enterprise security frameworks and regulatory requirements.Design and implement comprehensive data cataloguing procedures to improve data discoverability and usability. Integrate cataloguing processes with existing data governance frameworks to maintain continuity and compliance.Recommend and oversee the implementation of new tools and technologies related to ingestion, storage, processing, handling, security, and cataloguing. Design and plan to ensure seamless integration and minimal disruption during technology updates.Collaborate on the ongoing maintenance and provide technical support for legacy data ingestion pipelines throughout the uplift project. Ensure legacy systems remain stable, reliable, and efficient during the transition periodWork closely with the R&D IT team, data governance groups, and other stakeholders for coordinated and effective implementation of architectural updates. Collaborate in the knowledge transfer sessions to equip internal teams to manage and maintain the new architecture post-project. Bachelors degree in computer science, Information Technology, or a related field with equivalent hands-on experience.Minimum 10 years of experience in solution architecture, with a strong background in data architecture and enterprise data managementStrong understanding of cloud-native platforms, with a preference for AWS. Knowledgeable in distributed data architectures, including services like S3, Glue, and Lake Formation.Proven experience in programming languages and tools relevant to data engineering (e.g., Python, Scala). Experienced with big data technologies like: Hadoop, Cassandra, Spark, Hive, and Kafka. Skilled in using querying tools such as Redshift, SparkSQL, Hive, and Presto. Demonstrated experience in data modeling, data pipelines development and data warehousing. Infrastructure and Deployment: Familiar with Infrastructure-as-Code tools, including Terraform and CloudFormation. Experienced in building systems around the CI/CD concept. Hands-on experience with AWS services and other cloud platforms.
