Description

You will own the design and implementation of scalable analytics engineering pipelines using dbt Cloud, ensuring modularity, reusability, testing, and governance.

Responsibilities

• Design scalable and performant data workflows on Databricks using Delta Lake and Unity Catalog.
• Translate business needs into data models, semantic layers, and shared assets by partnering with Data Product and Value Stream teams.
• Implement data quality checks, CI/CD pipelines, and version control for analytics engineering projects.
• Contribute to architecture and design reviews across data initiatives to enforce best practices.
• Document lineage, metadata, and access patterns to ensure data discoverability and compliance.

Required Skills

• 5+ years of experience in data architecture, analytics engineering, or data engineering roles.
• Practical experience building transformation pipelines using dbt Cloud (models, tests, documentation, macros).
• Hands-on experience with Databricks and AWS.
• Strong proficiency in SQL, with familiarity using Python in data workflows.
• Solid understanding of data modeling principles, data quality techniques, and pipeline orchestration.
• Experience with agile delivery practices and CI/CD pipelines using tools like GitHub Actions or Databricks repos.
• Knowledge of Data Architecture, Aws, Databricks, Dbt, Python, Github, Sql, Ci/cd Pipelines.

Key Skills

Education

Any Gradute