Director - Data Solution Architect

You will be responsible for developing, maintaining, and testing data solutions with a wide variety of data platforms including relational databases, big data platforms and no-sql databases. You will collaborate with BI visualization experts, Industry SMEs, Data scientists and client Experts to drive data related projects. You will be responsible for Modelling the Data Lake. You will develop various data ingestion transformation routines to acquire data from external data sources. You will be involved in securing access to the data based on appropriate rights, implementing data quality routines and mechanisms to flag bad data for correction, and building QA and automation frameworks to monitor daily ingestion of data and provide alerts on errors and other problems.

Required Skills :

- 16+ years of experience in a Data Engineering/Architecture or similar role

- BE/B.Tech or Advanced degree in a relevant field (Computer Science and Engineering, Technology and related fields)

- Expertise in architecting and designing for Data Solutions, Security Constraints, Resiliency, High-Availability, Fault Tolerance, and Scalability in the context of GCP Cloud

- Strong experience with various architecture patterns like Data lake, EDW, Data Mesh, Data Vault

- Has Led Enterprise Architecture and Solutioning Efforts to Define and Develop Big Data Components

- Deep Knowledge of Best Practices Through Relevant Experience Across Data-Related Disciplines and Technologies, Particularly For Enterprise-Wide Data Architectures, Data Management, Data Governance And Data Warehousing

- Establish governance and enforce quality standards for cloud software and infrastructure architectures (IaaS, PaaS and SaaS)

- Experience in cloud replication strategies and architecture, as well as promoting a DevOps culture within the organization to support the CI/CD deployment process. Demonstrated advanced knowledge of native GCP tools

- Architect data integrations solutions in both batch and real-time to support functional and non-functional requirements of data projects.

- Architect and design framework components for standardization and productivity improvement.

- Architect and design solutions to advance data quality, metadata, data security, and data integration