Snowflake Data Engineer

Job Description

Hiring Sr. Data Engineer & Operation Data Engg Lead for Product MNCAs a hiring partner we are looking forThe Data Engineers who will be responsible for the hands-on development, maintenance, and optimization of robust, end-to-end 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.interested candidates can share word format resume with details at : hidden_emailJob Title: Sr Data Engineer - AnalyticsExperience : 8 Yrs ( 3-5 Yrs Relevant Exp in Data Engg)Location:Chennai# Purpose:The Data Engineer is responsible for the hands-on development, maintenance, and optimization of robust, end-to-end 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,# Key Skills : ETL,Data pipeline designing,DBT (Data build tool),Snowflake,data vault 2.0,Azure Data factory,ADLS,ADF,Python,Data lake Storage,data pipeline,data processing,data engineering,automated data ingesion,ETL,SQL,Python,data validation,Data movement,CI/CD tools,AI engineering using Git,Copilot,ChatGPT## Must Have :
• Hands on Real time Working exp in Snowflake,DBT,Data Vault 2.0,Azure Data Factory,ADLS,Data Engineering & AI Engineering
# Highlights
• Data Transformation & Modeling using DBT-Data Build tool,ETL,SQL transformations,Data vault 2.0.
• AI Engineering using GitHub Copilot, ChatGPT to generate the code
• 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.
• Tools/Technologies: Snowflake, dbt, Azure (Data Factory, ADLS), SQL, Python, Git, CI/CD tools, AI-assisted coding tools.
• Strong proficiency in writing complex, optimized SQL and solid scripting skills in Python.
# Responsibilities :
• Build and maintain scalable, automated data ingestion and procesing 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, ChatGPT) 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.
# Experience :
• Bachelors degree in Computer Science, Information Technology, Engineering, or a related field.
• Experience: 3-5 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.

Keyskills :
snowflakeazureetlpythondata processingdata transformationdata vaultdata solutionsdbt