Senior Data Engineer — Microsoft Fabric

GSMS, Incorporated; India; On-site; INR 2,800,000 - 3,800,000; Full time

Benefits offered by this job

Remote-work support

Medical insurance with family coverage

Life insurance

Paid leave and holidays

Job summary

GSMS in India is seeking a senior Data Engineer to migrate SQL Server and Azure Data Factory to Microsoft Fabric and to operate and advance the platform under the Lead Data Engineer.

You will translate legacy T-SQL and pipelines into Fabric solutions, build PySpark notebook transformations, implement ingestion and orchestration, and contribute to CI/CD and production delivery.

Qualifications

• 7+ years in data engineering with ownership of complex production delivery.
• Direct, hands-on production Microsoft Fabric experience including PySpark notebooks.
• Strong Python, PySpark, and T-SQL skills.
• Hands-on Azure Data Factory and SQL Server experience.
• Experience with data warehouse or platform migrations including reconciliation and production transition.
• Experience with Git, CI/CD, code review, and production incident resolution.
• Clear written and spoken English and ability to clarify business rules directly with users.

Responsibilities

• Translate complex legacy T-SQL and pipeline logic into reliable Fabric solutions.
• Build and troubleshoot PySpark notebook transformations and Fabric Warehouse models.
• Implement ingestion, incremental processing, orchestration, and recovery patterns.
• Work with quality engineers and business users to reconcile results and resolve differences.
• Contribute to code reviews, automated tests, CI/CD, and deployment practices under guidance.
• Improve reliability, performance, and capacity, transitioning to ongoing production support.
• Mentor engineers and document business logic, technical decisions, and procedures.
• Use AI-assisted engineering within established controls and review outputs.

Skills

Python

PySpark

T-SQL

Azure Data Factory

SQL Server

Git

CI/CD

English

Tools

Microsoft Fabric

Fabric Warehouse

Git

Azure

SQL

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 play a central, hands‑on role in migrating our SQL Server and Azure Data Factory environment to Microsoft Fabric, then take an ongoing role in operating and advancing the platform.

Working under our Lead Data Engineer, you’ll bring practical migration experience to complex implementation work. Our target architecture uses lake-based bronze and silver layers transformed through PySpark notebooks, with Fabric Warehouse serving the gold layer.

Assessment and planning are complete. Your initial focus will be migration execution, reconciliation, and production delivery.

What You'll Do

• Translate complex legacy T‑SQL and pipeline logic into reliable Fabric solutions.
• Build and troubleshoot PySpark notebook transformations and Fabric Warehouse models.
• Implement ingestion, incremental processing, orchestration, and recovery patterns.
• Work with quality engineers and business users to reconcile results and resolve differences.
• Contribute to code reviews, automated tests, CI/CD, and deployment practices under the Lead Data Engineer’s direction.
• Improve reliability, performance, and capacity efficiency, transitioning into ongoing production support as migration progresses.
• Mentor engineers and document business logic, technical decisions, and operational procedures.
• Use AI-assisted engineering within established controls, taking responsibility for reviewing and validating outputs.

What You'll Bring

• Typically 7+ years in data engineering, including ownership of complex production delivery.
• Direct, hands‑on production Microsoft Fabric experience, including PySpark notebooks and Fabric Warehouse.
• Strong Python, PySpark, and T‑SQL skills.
• Hands‑on Azure Data Factory and SQL Server experience.
• A substantial role in a data warehouse or platform migration, including reconciliation and production transition.
• Experience with Git, CI/CD, code review, and production incident resolution.
• Clear written and spoken English and the ability to clarify business rules directly with users.

Helpful Additional Experience

• Delta Lake tuning and maintenance.
• Automated data testing.
• Power BI semantic models and Direct Lake.
• Annual fixed gross salary of ₹28,00,000–₹38,00,000, 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 Arrangements

• 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.