Data Modeler – Cloud‑Native Architecture

About the role

We are looking for a Data Modeler to design and implement conceptual, logical and physical data models that support our cloud‑native architecture. You will work closely with data engineers, analysts and product teams to translate business requirements into scalable, high‑performance data structures on AWS.

Key responsibilities

• Design, build and maintain conceptual, logical and physical data models.
• Implement models using AWS services such as Redshift, RDS, S3, Glue, Athena and DynamoDB.
• Define and enforce modelling standards, naming conventions and metadata practices.
• Collaborate with business stakeholders to turn requirements into efficient data structures.
• Optimize models for performance, scalability and cost‑efficiency in the cloud.
• Ensure data integrity, lineage and governance through best‑practice modelling.
• Support secure, compliant and well‑documented data architecture design.
• Participate in data integration and transformation initiatives across systems.
• Maintain ER diagrams, data dictionaries and related documentation.

Required profile

• Bachelor’s degree in Computer Science, Information Systems, Data Science or a related field.
• 3+ years of hands‑on experience in data modelling and architecture.
• Strong knowledge of AWS data services (Redshift, RDS, S3, Glue, Athena, DynamoDB).
• Proficiency in SQL and data‑modelling tools such as ER/Studio, ERwin or dbt.
• Experience with relational, dimensional and NoSQL modelling.
• Familiarity with streaming platforms (Kafka, Kinesis) and lakehouse architectures.
• Experience working in Agile, cross‑functional teams.

Required skills

• AWS Redshift
• AWS RDS
• AWS S3
• AWS Glue
• AWS Athena
• AWS DynamoDB
• SQL
• ER/Studio
• ERwin
• dbt
• Kafka
• Kinesis
• Confluent Cloud
• Terraform
• CI/CD pipelines

What we offer

• Cloud‑native environment focused on innovation and learning.
• Professional development opportunities and AWS certification support.
• Competitive compensation and benefits.
• Flexible work options, including hybrid or remote arrangements.
• Collaborative culture with data‑driven impact.