Data Engineer

GSMS, Incorporated; India; On-site; INR 1,600,000 - 2,400,000; Full time

Benefits offered by this job

Remote-work support

Comprehensive medical insurance with家族

Life insurance

Paid leave and holidays

Job summary

GSMS is seeking a mid-level Data Engineer to keep production data pipelines running reliably and to help modernize our platform on Microsoft Fabric. You will work with SQL Server and Azure Data Factory, investigate failures, and contribute to the Fabric migration as workloads evolve.

The role requires 4+ years of hands-on data engineering experience, strong T-SQL, and collaboration with business users. The position offers fixed day-hour overlap with US colleagues and remote-work support.

Qualifications

• Typically 4+ years building and supporting production data pipelines or warehouses.
• Strong hands-on Azure Data Factory and SQL Server experience.
• Strong T-SQL skills, including understanding and modifying complex existing logic.
• Experience diagnosing production failures and data discrepancies.
• Understanding of dimensional modeling, incremental loads, and reconciliation.

Responsibilities

• Maintain and troubleshoot production Azure Data Factory pipelines and SQL Server workloads.
• Investigate failed jobs, late or missing data, and unexpected results, addressing underlying causes.
• Maintain complex T-SQL procedures, transformations, and dimensional models.
• Integrate business systems, external feeds, and changing file formats.
• Validate changes with quality engineers and business users before deployment.
• Contribute to migration tasks and develop practical skills in Fabric Warehouse and PySpark notebooks.
• Follow Git, pull request, code review, and deployment practices.
• Document business logic and support procedures.
• Use approved AI tools with appropriate review and testing.

Skills

Azure Data Factory

SQL Server

T-SQL

Data Warehousing

Git / Version control

Python / PySpark

English communication

Tools

Fabric

Python

PySpark

Job description

Employment: Full-time, dedicated to GSMS through an Employer of Record in India

Reports to: Lead Data Engineer

Working hours: 2:00–10:00 PM IST, fixed year-round

About GSMS

GSMS is the largest provider of generic pharmaceuticals to the US federal healthcare system, serving the Department of Veterans Affairs, Department of Defense, and other government healthcare organizations.

Data is central to how we compete—and win. Our data and analytics capabilities are a defining competitive advantage. The intelligence we develop about the government pharmaceutical market helps GSMS identify opportunities, shape our product portfolio, make competitive pricing decisions, and grow market share. Across sales, manufacturing, distribution, and daily operations, colleagues depend on our insights to decide where to act and how to succeed.

We’re embarking on a company-wide AI transformation.

Our 24-month implementation roadmap will bring AI and advanced analytics into how teams make decisions and get work done across GSMS. Modernizing our platform on Microsoft Fabric provides a foundation for self-service analytics, data and operational agents, and workflow automation. Within engineering, we’re integrating AI and large language models into a governed process for building, reviewing, and validating solutions.

You’ll join a dedicated GSMS team, work directly with business users, and take lasting ownership of solutions that shape how the company competes.

The opportunity

You’ll keep business-critical data pipelines running reliably while helping modernize the platform behind them.

Your initial focus will be SQL Server and Azure Data Factory: maintaining pipelines, investigating failures, and improving existing business logic. You’ll also contribute to our Fabric migration and transition into supporting the new environment as workloads move.

This is a mid-level role with meaningful production responsibility and opportunities to develop toward senior engineering responsibilities.

What you’ll do

• Maintain and troubleshoot production Azure Data Factory pipelines and SQL Server workloads.
• Investigate failed jobs, late or missing data, and unexpected results, addressing underlying causes.
• Maintain complex T-SQL procedures, transformations, and dimensional models.
• Integrate business systems, external feeds, and changing file formats.
• Validate changes with quality engineers and business users before deployment.
• Contribute to migration tasks and develop practical skills in Fabric Warehouse and PySpark notebooks.
• Follow Git, pull request, code review, and deployment practices.
• Document business logic and support procedures.
• Use approved AI tools with appropriate review and testing.

What you’ll bring

• Typically 4+ years building and supporting production data pipelines or warehouses.
• Strong hands-on Azure Data Factory and SQL Server experience.
• Strong T-SQL skills, including understanding and modifying complex existing logic.
• Experience diagnosing production failures and data discrepancies.
• Understanding of dimensional modeling, incremental loads, and reconciliation.
• Experience with Git and controlled deployment practices.
• Clear written and spoken English and confidence working directly with business users.
• Willingness and ability to develop Fabric, Python, and PySpark skills as the platform evolves.

Helpful additional experience

• Python or PySpark.
• Automated data testing.
• Data warehouse migrations.

Compensation and benefits

• Annual fixed gross salary of ₹16,00,000–₹24,00,000, based on relevant skills and experience.
• Additional incentive compensation based on individual and company performance.
• Comprehensive medical insurance with family coverage options.
• Life insurance.
• Paid leave and holidays.
• Remote-work support.

Working arrangement

• This is a dedicated, full-time position, with employment administered through an Employer of Record (EOR) in India.
• Your day-to-day work, team relationships, and priorities will be with GSMS.
• Working hours are 2:00–10:00 PM IST, fixed year-round, providing overlap with US colleagues. Production support takes place within these hours.
• You must be available during scheduled working hours and may not hold another full-time job concurrently. Any outside work must comply with the applicable employment agreement and conflict-of-interest policy.