Data Modeler

*US CIT OR GREEN CARD HOLDER ONLY!****

*Can not work with employers*

PRINCIPAL DUTIES AND RESPONSIBILITIES:

· Design and implement relational and dimensional data models for enterprise data warehouses.

· Develop conceptual, logical, and physical data models that align with business requirements and compliance standards.

· Perform data profiling and analysis to understand data quality, structure, and relationships.

· Build and optimize data models to facilitate ingestion and transformation pipelines into warehouse utilizing Airflow, Dataflow, Pub/Sub, Spark, and Python.

· Manage and process structured and semi-structured data formats, including JSON and complex data types (e.g., Struct).

· Apply expertise in data modeling, database design, and data architecture to ensure scalability and performance.

· Collaborate with product managers and stakeholders to design data products that deliver actionable insights.

· Ensure and enforce data quality, lineage, and governance across all data assets.

· Define and document data models, relationships, pipelines, and processes to promote transparency and maintainability.

POSITION SPECIFICATIONS:

• Bachelor’s or master’s degree in computer science, Data Engineering, Information Systems, or related STEM field.

• 5 years of experience in data modeling, data governance and data Architecture roles.

• Hands-on experience with GCP, BigQuery, Dataflow, SQL, and Python.

• Define domain relationships and build connected entity models

• Strong understanding of normalization, dimensional modeling, and data warehousing.

• Familiarity with structured and semi-structured data handling.

• Attention to detail to ensure the accuracy of the data models and their ability to meet organizational needs.

• Understanding of retail banking/Credit Card data domains and regulatory requirements.

• Proficiency in SQL and data modeling tools (e.g., Wherescape, ERwin, ER/Studio)

• Excellent communication and documentation skills.

Nice to Have:

• Certifications in GCP Professional Data Engineer or Architect.

• Experience with data governance frameworks and metadata management.

• Exposure to data product lifecycle and data mesh principles.