Purpose
- The candidate is responsible for designing, creating, deploying, and maintaining an organization's data architecture.
- To ensure that the organization's data assets are managed effectively and efficiently, and that they are used to support the organization's goals and objectives.
- Responsible for ensuring that the organization's data is secure, and that appropriate data governance policies and procedures are in place to protect the organization's data assets.
Key Responsibilities
Responsibilities will include but will not be restricted to:
- Responsible for designing and implementing a data architecture that supports the organization's business goals and objectives.
- Developing data models, defining data standards and guidelines, and establishing processes for data integration, migration, and management.
- Create and maintain data dictionaries, which are a comprehensive set of data definitions and metadata that provide context and understanding of the organization's data assets.
- Ensure that the data is accurate, consistent, and reliable across the organization. This includes establishing data quality metrics and monitoring data quality on an ongoing basis.
- Organization's data is secure, and that appropriate data governance policies and procedures are in place to protect the organization's data assets.
- Work closely with other IT professionals, including database administrators, data analysts, and developers, to ensure that the organization's data architecture is integrated and aligned with other IT systems and applications.
- Stay up to date with new technologies and trends in data management and architecture and evaluate their potential impact on the organization's data architecture.
- Communicate with stakeholders across the organization to understand their data needs and ensure that the organization's data architecture is aligned with the organization's strategic goals and objectives.
Mandatory Skills
- AWS Cloud Services
- Compute EC2
- Storage - S3 mandatory Other storage components
- AWS Services Like IAM,S3.
- Programming Python, Pyspark, Lamda.
- Knowledge on ETL Glue (Mandatory), DMS.
- Databases Data Bricks , RDBMS skills added advantages like Oracle, SQLServer, MPP databases like Snowflake, Redshift .
- Knowledge on Data modelling and ETL process is mandatory.
- Architecture Data Mesh, Medallion and EDW - Data Modelling.
Technical requirements
- Bachelor's or master's degree in Computer Science or a related field.
- Certificates in Database Management will be preferred.
- Expertise in data modeling and design, including conceptual, logical, and physical data models, and must be able to translate business requirements into data models.
- Proficient in a variety of data management technologies, including relational databases, NoSQL databases, data warehouses, and data lakes.
- Expertise in ETL processes, including data extraction, transformation, and loading, and must be able to design and implement data integration processes.
- Experience with data analysis and reporting tools and techniques and must be able to design and implement data analysis and reporting processes.
- Familiar with industry-standard data architecture frameworks, such as TOGAF and Zachman, and must be able to apply them to the organization's data architecture.
- Familiar with cloud computing technologies, including public and private clouds, and must be able to design and implement data architectures that leverage cloud computing.
Qualitative Requirements
- Able to effectively communicate complex technical concepts to both technical and non-technical stakeholders.
- Strong analytical and problem-solving skills.
- Must be able to inspire and motivate their team to achieve organizational goal.