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.
Detailed Job Description for Solution Architect at PAN India:
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 Optimization Evaluate 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 period Work 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.
Required Skills:
· Bachelor’s 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 management
· Strong 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, Spark SQL, 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.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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