
Principal Data Architect
2 days ago
Role & responsibilities
• Minimum 15 years of experience
• Deep understanding of data architecture principles, data modelling, data integration, data governance, and data management technologies.
• Experience in Data strategies and developing logical and physical data models on RDBMS, NoSQL, and Cloud native databases.
• Decent experience in one or more RDBMS systems (such as Oracle, DB2, SQL Server)
• Good understanding of Relational, Dimensional, Data Vault Modelling
• Experience in implementing 2 or more data models in a database with data security and access controls.
• Good experience in OLTP and OLAP systems
• Excellent Data Analysis skills with demonstrable knowledge on standard datasets and sources.
• Good Experience on one or more Cloud DW (e.g. Snowflake, Redshift, Synapse)
• Experience on one or more cloud platforms (e.g. AWS, Azure, GCP)
• Understanding of DevOps processes
• Hands-on experience in one or more Data Modelling Tools
• Good understanding of one or more ETL tool and data ingestion frameworks
• Understanding of Data Quality and Data Governance
• Good understanding of NoSQL Database and modeling techniques
• Good understanding of one or more Business Domains
• Understanding of Big Data ecosystem
• Understanding of Industry Data Models
• Hands-on experience in Python
• Experience in leading the large and complex teams
• Good understanding of agile methodology
• Extensive expertise in leading data transformation initiatives, driving cultural change, and promoting a data driven mindset across the organization.
• Excellent Communication skills
• Understand the Business Requirements and translate business requirements into conceptual, logical and physical Data models.
• Work as a principal advisor on data architecture, across various data requirements, aggregation data lake data models data warehouse etc.
• Lead cross-functional teams, define data strategies, and leverage the latest technologies in data handling.
• Define and govern data architecture principles, standards, and best practices to ensure consistency, scalability, and security of data assets across projects.
• Suggest best modelling approach to the client based on their requirement and target architecture.
• Analyze and understand the Datasets and guide the team in creating Source to Target Mapping and Data Dictionaries, capturing all relevant details.
• Profile the Data sets to generate relevant insights.
• Optimize the Data Models and work with the Data Engineers to define the Ingestion logic, ingestion frequency and data consumption patterns.
• Establish data governance practices, including data quality, metadata management, and data lineage, to ensure data accuracy, reliability, and compliance.
• Drives automation in modeling activities Collaborate with Business Stakeholders, Data Owners, Business Analysts, Architects to design and develop next generation data platform.
• Closely monitor the Project progress and provide regular updates to the leadership teams on the milestones, impediments etc.
• Guide /mentor team members, and review artifacts.
• Contribute to the overall data strategy and roadmaps.
• Propose and execute technical assessments, proofs of concept to promote innovation in the data space.
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