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Chennai · On-site · 6-9 Yrs · Oct 14
1 views
1 open role0 posted in 7d1 in 30d
Hiring: Engineering
Job description
Overview
Data Engineer (Azure, Snowflake, dbt) | 6-10 Years
Responsibilities
- 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.
- 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.
- 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.
Qualifications
- 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 have
- 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.
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Job application FAQ
Last updated 14 October 2026
- How do I apply for Data Engineer (Azure, Snowflake, dbt) at The Digital Loom?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. The Digital Loom may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Data Engineer (Azure, Snowflake, dbt) role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Data Engineer (Azure, Snowflake, dbt) remote or on-site in Chennai, Tamil Nadu?
- This listing is marked on_site with location Chennai, Tamil Nadu. Confirm details on the job description before applying.
- What skills matter for this Data Engineer (Azure, Snowflake, dbt) role at The Digital Loom?
- This is a mid-level Data Engineer (Azure, Snowflake, dbt) role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.