About the job
Key Responsibilities
- Design, develop, and maintain logical and physical data models, ensuring data integrity, consistency, accuracy and optimize the performance.
- Collaborate with data engineering teams to define and implement data structures that support microservices-based architectures.
- Develop and maintain mapping tables, ensuring accurate and efficient data integration.
- Create and enforce data modeling standards, best practices, and governance policies.
- Ensure data quality by implementing validation rules, data cleansing processes, and optimization techniques.
- Work closely with ETL teams to define and implement data flows and transformation logic.
- Support data warehousing efforts by designing models that align with the organization's reporting and analytics needs.
- Perform reverse engineering of existing data models and recommend improvements.
- Expertise in data modeling techniques, including ERD (Entity-Relationship Diagrams), dimensional modeling, and normalization/denormalization processes.
- Strong experience with data warehousing concepts and architectures, including star and snowflake schemas.
- Proficiency in SQL for data querying, transformation, and optimization
- Familiarity with ETL processes and tools (e.g., AWS Glue, Informatica, Talend).
- Experience in data quality management, including data profiling, validation, and cleansing.
- Understanding of data governance practices and metadata management.
- Experience with cloud-based data warehousing solutions, particularly on AWS.
- Familiarity with microservices architecture and how it influences data modeling.
- Experience with Data Modeling tools such as Erwin, IBM Infosphere etc