DATA ARCHITECT

The Data Architect is accountable for designing, developing, and maintaining the corporate Data to meet business demands. The Data Architect is responsible for converting business requirements to Enterprise data solutions which include data modeling, data engineering and analytics solutions.? This role is expected to have knowledge and experience at gathering and translating business requirements into industry standard data solutions., * Builds exemplary data architecture solutions in terms of efficiency, stability, extensibility, and the ability to evolve over time.

• Defines data architecture framework, standards and principles for modeling, metadata, data catalog, and data security.
• Builds enterprise standard data models for analytics, reporting and application usage.
• Leads architecture, implementation, and operations of platforms and tools for data engineering and analytics projects.
• Architect, Design, and develop data pipelines to ingest from relational databases (Oracle, SQL Server, DB2, Aurora), file shares, and web services into AWS data stores like S3 data lake, RDS and Snowflake data warehouse.
• Educates and trains counterparts and junior staff in data engineering and analytics, conduct POCs and apply domain understanding to address new data and analytics requirements.
• Participates in designing, developing, supporting ETL processes employing industry standards and best practices to enhance loading of data to the EDW.
• Participates in requirements gathering, system design, and data design.
• Participates in all aspects of the software life cycle using Agile development methodologies.
• Performs other job-related duties as assigned or apparent.

• Experience architecting, designing, and developing large scale data architecture solutions utilizing a mixture of cloud and on-prem database platforms.
• Experience with platform engineering, tooling & standards to improve the productivity and quality of data solutions.
• Experience designing and architecting data warehouses and data lakes.
• Experience converting business requirements into logical and physical data models suitable for analytics and application use cases.
• Data Virtualization or logical Data warehouse implementation using Denodo or similar technologies.
• Experience building cloud Data Warehouse solutions using Snowflake and ELT tools like DBT, Informatica IICS or wherescape.
• Excellent knowledge of modelling NoSQL database like DynamoDB, MongoDB.
• Working knowledge of AWS services for Data Engineering (S3, Kinesis, Lambda, Athena, EMR, Cloud Watch, SNS, SQS).
• Background in Business Intelligence applications like Qlik Sense, Tableau, or PowerBI.
• Experience with analytics tools like SAS, R, Python, and other advanced statistical software.
• Good understanding Machine Learning and Artificial Intelligence, worked on platforms like Sagemaker, Anaconda, Databricks, DataRobot.
• Experience with Git/GitHub, branching, and other modern source code management methodologies.
• Experience with DevOps and Terraform is a plus.
• Ability to multi-task effectively.
• Ability to work collaboratively as part of an Agile Team.

MINIMUM QUALITIFICATIONS:?

• Bachelor’’s degree in IT, Engineering, Statistics, or related field.
• Minimum of 8 years of experience in designing, developing, planning and executing Enterprise Data technology solutions, tools, operations and support.

Minimum of 7 years of experience in one of the following: data design, integration, data engineering, data management, analytics, and data modeling.