Description

You will lead the design and implementation of modern data platforms.

Responsibilities

• Design, develop, and optimize ELT pipelines using Databricks (PySpark), Azure Data Factory (ADF), or Synapse.
• Build and manage data marts and analytics solutions on Snowflake, leveraging features like Streams, Tasks, Clustering, and RBAC.
• Develop modular data models and transformations using dbt; manage orchestration via Dagster, Airflow, or Prefect.
• Implement automated data validation using Great Expectations or dbt tests to ensure data quality in production.
• Build and manage infrastructure using Terraform or Bicep, including deployment pipelines via GitHub Actions, Azure DevOps, or similar tools.
• Lead Agile ceremonies and mentor junior engineers, championing engineering best practices.

Required Skills

• 6+ years of experience in Data Engineering with production-level Azure Databricks and PySpark.
• Hands-on experience with dbt, Dagster, or similar tools for transformation and orchestration.
• Strong SQL and Python programming skills with emphasis on modularity and scalability.
• Demonstrated ability to deploy infrastructure as code (Terraform/Bicep) and CI/CD workflows.
• Experience with Snowflake for building data marts and analytics.
• Proficiency in Git for version control and team collaboration.
• Experience with ELT Pipelines, ADF, Synapse, GitHub Actions, Azure DevOps.
• Familiarity with financial services use cases (capital markets, asset/wealth management).

Key Skills

Education

Any Graduate