Principal Data Architect - Data Modelling

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 datadriven 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.