Analyse current state of inventory of data sources, discover ETL activities & processes adopted, understand data quality & lineage.
Discover and analyse Metadata, Master data and Reference data
Analyse Data Access Management, self-service BI Practices in a system
Analyse data life cycle (Important points of access, acquire, transport, store, query, manage, secure, and share)
Discover current state of Databases Availability, Backup, Recovery Mechanism
Understand the system of data virtualisation and related tools like Denodo'
Evaluate current state and recommend future roadmap for the organisation data lake, data warehousing and cloud storage requirements (Azure, Snowflake, AWS for semi-structured and unstructured data)
Design data pipeline architecture for data lake & data warehouse (like Azure Data Factory)
Evaluate ETL run-time and recommend suitable schema designs.
Recommend cloud-based data warehouse and analytics solution (Azure Data Factory, Synapse Analytics and Data bricks, AWS services, Snowflake)
Analyse structural requirements for new software, hardware and applications
Understand business & technical requirements to migrate data from legacy systems to new solutions
Build data models for database structures, analytics and AI applications.
Improve & elaborate system performance parameters
Evaluate & Optimize new and current database systems
Provide insight into the changing database storage and utilization requirements and offer suggestions
Integrate new systems and functions like security, performance, scalability, reliability and data recovery.
Collaborate in a data strategy that meets the industry requirements
Envision data pipelines and how data will flow through the enterprise
Evaluate current data management technologies, policies and suggest improvements
Design, document, build and implement database architectures and applications.
Develop measures that ensure data accuracy, integrity and accessibility.
Ensure that the data architecture is scalable and maintainable
Suggest suitable data architecture landscape for integration and scaling
Understand granular details of current MIS
Requirements and skills
Bachelor's / Master's Degree in Computer Engineering or degree / certification in data architecture
Proven work experience as a Data Architect, Data warehouse designer, Data Engineer, Data Scientist, Data Analyst or similar role
In-depth understanding of database structure principles
Familiarity with data virtualisation tools
Data management and reporting technologies, data visualization and structured / unstructured data management
Strong business and communication skills
Good understanding of key architecture concerns such as availability, scalability, operability and maintainability
Skills Required
Data Architect, Etl, Aws
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Data Architect • Hyderabad / Secunderabad, Telangana, Noida, Chandigarh
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