Data Engineer

Tristha Global Pvt. Ltd.; Chennai District; On-site; INR 1,500,000 - 3,000,000; Full time

Job summary

Tristha Global Pvt. Ltd. is seeking a data engineering professional to build end-to-end data solutions for software testing, automation, and BFSI use cases. You will design and implement scalable ETL/ELT pipelines, integrate data from diverse enterprise systems, and own the data lifecycle from architecture to production support.

The role emphasizes data quality, synthetic data generation, and AI/ML data preparation, with focus on real-time and batch processing and analytics-ready datasets.

Qualifications

• Strong experience designing scalable ETL/ELT pipelines.
• Experience integrating data from diverse enterprise systems.
• Ownership of data engineering lifecycle from design to production support.

Responsibilities

• Build end-to-end data engineering solutions for data driven use cases.
• Develop and optimize ETL/ELT pipelines at scale.
• Ensure data quality, validation and governance across platforms.
• Provide production support and performance tuning for data workflows.

Skills

ETL/ELT pipelines

Data integration

Data quality

Test data management

Synthetic data

AI/ML data prep

Feature engineering

Real-time processing

Batch processing

Analytics datasets

Data platforms

Job description

The role involves building end-to-end data engineering solutions for software testing, automation, and BFSI domain use cases, including:

• Enterprise data integration and migration


• ETL/ELT pipeline development


• Data quality and validation frameworks


• Test data management and synthetic data generation


• AI/ML data preparation and feature engineering


• Real-time and batch data processing


• Analytics-ready data platforms and reporting datasets

The ideal candidate will have strong practical experience designing and implementing scalable ETL/ELT pipelines, integrating data from diverse enterprise systems, and optimizing large-scale data processing workloads. They should be capable of owning the complete data engineering lifecycle—from solution design and architecture through development, deployment, performance optimization, and production support.