Python ETL Data Testing Lead

Trigent Software; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Trigent Software in Bengaluru, India, seeks a Lead ETL Test Engineer to lead end-to-end testing across data warehouses, ETL pipelines and modern data platforms, ensuring data quality, integrity and performance at scale.

The role requires deep technical proficiency in big data tools, strong programming skills and cloud-native experience, with a focus on data validation, DW/ETL testing and scalable data platforms.

Qualifications

• Expertise in ETL testing and data validation across complex pipelines.
• Strong proficiency in Python programming.
• Hands-on experience with PySpark and/or Scala for large-scale data processing.
• Advanced knowledge of SQL, data modeling, and database testing (SQL & NoSQL).
• Experience with data warehouses and data lakes (e.g., Snowflake).
• Strong experience with Databricks.
• Deep understanding of Big Data ecosystems.
• Experience in testing data pipelines and ETL workflows.
• Strong understanding of data modeling techniques.
• Input/output validation for ML pipelines.

Skills

ETL testing

Data validation

Python programming

PySpark

Scala

SQL

Data modeling

Database testing

Big Data ecosystems

Data pipelines

ETL workflows

ML pipelines IO validation

Tools

Snowflake

Databricks

Job description

We are seeking a highly experienced Lead ETL Test Engineer with strong expertise in data validation, data pipelines, and big data ecosystems. The ideal candidate will lead end-to-end testing strategies across data warehouses, ETL pipelines, and modern data platforms, ensuring data quality, integrity, and performance at scale. This role requires deep technical proficiency in big data tools, strong programming skills, and experience with cloud-native environments.

Primary Skills

• Expertise in ETL testing and data validation across complex pipelines
• Strong proficiency in Python programming
• Hands‑on experience with PySpark and/or Scala for large-scale data processing
• Advanced knowledge of SQL, data modeling, and database testing (SQL & NoSQL)
• Experience with data warehouses and data lakes (e.g., Snowflake)
• Strong experience with Databricks
• Deep understanding of Big Data ecosystems
• Experience in testing data pipelines and ETL workflows
• Strong understanding of data modeling techniques
• Input/output validation for ML pipelines