BuildMSAGCAAI1

Job Description:

Experience: Minimum of 12 years in data management data engineering or related fields with 5-7 years in a dedicated data engineering or data architecture role.

Data Modeling and Architecture: Proven experience in designing and implementing data architectures for scalability and performance including dimensional modeling and schema design and in Datawarehousing projects

SQL Proficiency: Advanced knowledge of SQL for data querying transformation and database management tasks.

Smart analytics GenAi and Machine Learning experience

Required Skills

Data Warehousing: Hands-on Datawarehousing solutions preferrable on cloud data warehousing platforms such as AWS Redshift or Snowflake with at least one completed project showcasing independent implementation.

ETL Development: Proficiency in building and managing ETL workflows using platforms such as Informatica AWS Glue or other SQL-based ETL tools.

Database Management and Optimization: Strong skills in database management query optimization and performance tuning for large datasets.

Smart analytics GenAI and Machne Learning experience

Project Management: Demonstrated ability to independently manage data engineering projects from planning and design to execution and optimization.

Desired Qualifications

Data Transformation and Processing: Expertise in data cleansing transformation and structuring techniques to prepare data for analytics solutions

Cloud Computing and Infrastructure: Working knowledge of key AWS services (e.g. S3 Lambda and Glue) with a focus on integrating these services within a scalable data architecture.

Terraform and CI/CD pipeline

Advanced Data Warehouse Concepts: Familiarity with best practices for data warehousing including star and snowflake schemas and experience in implementing data marts or data lakes.

Nice-to-Have Skills

Data Security and Compliance: Understanding of data security practices including encryption access control and compliance particularly in cloud environments.

Business Intelligence and Reporting: Basic exposure to BI tools such as Power BI with an understanding of how data architectures support dashboard and reporting needs.

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