Senior Python Data Engineer (Azure) Pan India Hybrid

Trigent Software Private Limited

Job Location:

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: 3 hours ago

Vacancies: 1 Vacancy

Job Summary

Experience: 7 Years
Location: Pan India
Work Mode: Hybrid
Shift: General

Role Overview

We are looking for a Senior Python Data Engineer with strong hands-on expertise in Python Pandas PySpark and Azure-based data platforms. The role involves designing scalable ETL pipelines working with structured and unstructured data and building modern data solutions including vector databases to support advanced analytics and RAG-style workloads.

Primary Responsibilities

Design build and maintain robust scalable ETL pipelines for batch and large-scale data processing
Develop advanced Python-based data engineering solutions using Pandas and PySpark
Implement data ingestion and processing workflows using Azure Synapse and related Azure services
Apply data modeling and data quality best practices including schema design validation and testing
Work with SQL and file-based data sources (SQL Server PostgreSQL CSV JSON Parquet)
Automate manual data ingestion and processing tasks through scripts jobs and orchestration-ready workflows
Collaborate with cross-functional teams and clearly communicate progress risks and blockers
Follow best practices for version control using Git and GitHub (branching PRs code reviews)

Mandatory Skills

Strong proficiency in Python for data engineering
Hands-on experience with Pandas and PySpark
Solid experience with Azure Cloud Services especially Azure Synapse
Strong understanding of ETL processes data modeling and data quality standards
Experience working with structured and unstructured data
Familiarity with MongoDB Qdrant and vector database concepts (embeddings similarity search RAG patterns)
Working knowledge of Git and GitHub

Desired / Good-to-Have Skills

Orchestration tools: Conductor Airflow Prefect Azure Data Factory
Azure DevOps (ADO) boards and Scrum workflow discipline
Local development optimization: Docker reproducible dev environments Makefiles
Performance tuning in Spark / Synapse (partitioning caching join strategies)
Vector search best practices: HNSW indexing hybrid search payload design filtering
Observability for data pipelines: logging metrics alerting
Event-driven and scheduled ingestion automation patterns
Strong collaboration mindset and proactive ownership of shared initiatives

Experience: 7 Years Location: Pan India Work Mode: Hybrid Shift: General Role Overview We are looking for a Senior Python Data Engineer with strong hands-on expertise in Python Pandas PySpark and Azure-based data platforms. The role involves designing scalable ETL pipelines working with structu...

Experience: 7 Years
Location: Pan India
Work Mode: Hybrid
Shift: General

Role Overview

Primary Responsibilities

Design build and maintain robust scalable ETL pipelines for batch and large-scale data processing
Develop advanced Python-based data engineering solutions using Pandas and PySpark
Implement data ingestion and processing workflows using Azure Synapse and related Azure services
Apply data modeling and data quality best practices including schema design validation and testing
Work with SQL and file-based data sources (SQL Server PostgreSQL CSV JSON Parquet)
Automate manual data ingestion and processing tasks through scripts jobs and orchestration-ready workflows
Collaborate with cross-functional teams and clearly communicate progress risks and blockers
Follow best practices for version control using Git and GitHub (branching PRs code reviews)

Mandatory Skills

Strong proficiency in Python for data engineering
Hands-on experience with Pandas and PySpark
Solid experience with Azure Cloud Services especially Azure Synapse
Strong understanding of ETL processes data modeling and data quality standards
Experience working with structured and unstructured data
Familiarity with MongoDB Qdrant and vector database concepts (embeddings similarity search RAG patterns)
Working knowledge of Git and GitHub

Desired / Good-to-Have Skills

Orchestration tools: Conductor Airflow Prefect Azure Data Factory
Azure DevOps (ADO) boards and Scrum workflow discipline
Local development optimization: Docker reproducible dev environments Makefiles
Performance tuning in Spark / Synapse (partitioning caching join strategies)
Vector search best practices: HNSW indexing hybrid search payload design filtering
Observability for data pipelines: logging metrics alerting
Event-driven and scheduled ingestion automation patterns
Strong collaboration mindset and proactive ownership of shared initiatives