Data Engineer (Azure, Snowflake, dbt)

Data Engineer (Azure, Snowflake, dbt) | 6-10 Years
Description:
Data Engineer is responsible for the hands-on development, maintenance, and optimization of robust, end-to-end (E2E) analytics data pipelines. You will leverage a modern cloud stack (Azure, Snowflake, dbt) to ingest and transform data according to Data Vault 2.0 standards, while actively utilizing AI-assisted development tools to write high-quality code faster and more efficiently.
Responsibilities
Build and maintain scalable, automated data ingestion and processing pipelines using Azure, dbt, Snowflake to extract data from various source systems and load it into Snowflake for further processing.
Data Transformation & Modeling: Use dbt (data build tool) to develop modular, testable SQL transformations. Implement physical Data Vault 2.0 structures (Hubs, Links, Satellites) based on architectural designs.
AI-Assisted Engineering: Actively use AI coding assistants (e.g., GitHub Copilot / Cursor) to generate boilerplate code, write dbt tests, draft documentation, and troubleshoot SQL/Python scripts, significantly accelerating your delivery cycle.
Quality & Testing: Ensure high data quality by writing comprehensive dbt tests and implementing automated data validation checks within the E2E architecture.
Collaboration: Work closely with the Tech Lead, Data Architect, and business analysts in an Agile environment to understand requirements and deliver reliable data sets for downstream reporting.
Typical Activities:
Writing and optimizing SQL queries and Python scripts for data extraction and transformation.
Configuring Azure Data Factory, Snowpark Python pipelines for secure, scheduled data movement.
Developing dbt models, macros, and tests to populate the Snowflake Data Vault.
Collaborating in daily Scrum meetings and participating in code reviews with the Tech Lead.
Requirements
Experience: 6-9 years of hands-on experience in Data Engineering or Database Development.
Technical Expertise: Strong proficiency in writing complex, optimized SQL and solid scripting skills in Python.
Hands-on experience building pipelines in Microsoft Azure (ADF, Data Lake Storage).
Practical experience developing and performance-tuning within Snowflake.
Experience using dbt for data transformation, testing, and documentation.
Familiarity with incorporating AI-assisted development tools (like GitHub Copilot) into daily coding workflows.
Understanding of Data Vault 2.0 concepts (Hubs, Links, Satellites) and how to populate them.
Nice to Haves:
Microsoft Certified: Azure Data Engineer Associate or SnowPro Core Certification.
Experience with CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) and version control (Git).
Exposure to building dimensional models (Star Schemas) on top of a Data Vault.
Email - abhishek.goswami@thedigitalloom.com

Work arrangement
Hybrid