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Module Lead — Fabric Data Engineering
WinWire —Hyderabad, Telangana
- Azure
- SQL
- Agile
- Health insurance

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Module Lead — Fabric Data Engineering
WinWire —Hyderabad, Telangana
As an Employer of Choice, WinWire offers an exceptional workplace culture, industry recognition, and an unwavering commitment to employee growth.

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Module Lead — Fabric Data Engineering

WinWire -
Hyderabad, Telangana

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Job details

Benefits

Health insurance

Qualifications

FTP
Azure
SQL
Unity
Agile
AI
Communication skills
Python

Full job description

Experience: 5 to 8 years

Role Summary

We are looking for a Senior Data Engineer with strong Microsoft Fabric and Python skills to build and deliver production-grade data pipelines for a specialty medical stop loss insurance enterprise’s claims modernization platform. You will own end-to-end pipeline development across assigned workstreams — ingestion, transformation, data quality, and Gold layer views — working as part of a focused delivery team under direct Technical Lead guidance. This is a build role: you write code, ship pipelines, and own the quality of your workstream output.

Why This Role Matters

This role is essential in accelerating enterprise data modernization by enabling robust, governed, and scalable Azure Lakehouse platforms that support analytics, operational insights, and AI-driven business transformation initiatives.

What You’ll Do

Ingestion Pipeline Development
Build Fabric Data Factory pipelines for batch file intake from assigned Phase 1 TPAs — handling xlsx, csv, and txt files across varying source channels (email, FTP, secure portal)
Implement schema registry alias mappings for your assigned TPA file variants — handling known format differences and flagging schema drift for Technical Lead review
Medallion Transformations — Bronze, Silver & Gold
Implement Bronze layer Delta Lake tables with immutable append-only transaction history and correct partition and retention configurations
Build Silver layer transformations per the canonical data model — code standardization (diagnosis, procedure, revenue), member/subscriber normalization, and adjustment/void/reversal handling in Pyspark/SQL
Data Quality & Exception Handling
Implement DQ rule sets for assigned TPA workstreams — record-level validation, cross-field checks, and business rule enforcement using WinAIDM Data Quality Agent
Build exception triage outputs: structured failure reason codes, quarantine routing, and failed record logging integrated with the review queue UI backend
Historical Data Migration
Participate in the historical migration pilot for assigned TPAs — apply current-state pipeline patterns to 7+ years of historical data and document data quality findings
Execute Bronze archival or full reprocessing path per the go/no-go decision; ensure historical records are correctly partitioned and labeled in the Lakehouse
Collaboration & Standards
Participate in daily standups, sprint planning, and code reviews — contributing to and receiving feedback from the Technical Lead
Follow WinWire’s WinAIDM accelerator standards for pipeline development: using AI-assisted ingestion, quality, and transformation agents for consistent implementation patterns

Tech Stack Snapshot

Fabric Data Factory pipelines & Python and SQL Databricks, Azure AI Services, Unity Catalog, One Lake Lakehouse’s, Python, and Delta Lake patterns.

Must-Have Skills

5+ years in data engineering with hands-on experience building and maintaining production-grade data pipelines
Practical, production-level experience in Microsoft Fabric — Fabric Data Factory pipelines, One Lake Lakehouse’s, and Delta Lake patterns (not just learning-lab exposure)
Expert Python and SQL — you write complex transformation logic, debug data issues independently, and review your own code before submitting for review
Experience building data quality validation: schema validation, reconciliation, record-level checks, and exception/quarantine workflows
Solid understanding of medallion (Bronze / Silver / Gold) architecture — you have built at least one layer end-to-end in a real project
Familiarity with Azure AI Services — Azure Document Intelligence or similar for extracting structured data from documents or semi-structured files
Comfortable working in an Agile delivery cadence with Technical Lead direction and cross-time zone collaboration

Good to Have

Strong collaboration and communication skills to work effectively with diverse teams and stakeholders.

What Success Looks Like (6–12 Months)

We are seeking a highly skilled Data Engineering specialist with above mentioned Primary Skills to join our dynamic team.
A successful implementation of Phase I and II of Claims Management Platform
Effectively Communicate and Collaborate with internal teams and customers to build code leveraging or building low level design documents aligning to standard coding principles and guidelines.

Why Join WinWire: Your Path to Professional Excellence in the Age of AI

As an Employer of Choice, WinWire offers an exceptional workplace culture, industry recognition, and an unwavering commitment to employee growth. Here is why top talent chooses us:

AI-First. Globally Recognized: Honored at the World Economic Forum in Davos for our pioneering "Agentic AI @ Scale" work, cementing our position as a forward-thinking, AI-first services firm shaping the future of enterprise technology.
Microsoft Gold Standard: A 6x Microsoft Global Partner of the Year Winner/Finalist — reflecting our consistent delivery of industry-leading solutions and our deep, trusted partnership with Microsoft.
Joining the NTT DATA Family: WinWire (Part of NTT DATA), a $30 billion global leader in AI, digital business, and technology services. This means greater career stability, broader client exposure, and access to a vast landscape of opportunities across a truly global organization.
Award-Winning Culture: Certified as a Best Place to Work® four times, our workplace culture is not just a talking point — it is a proven, recognized commitment to creating an environment where people genuinely thrive.
People-First Environment: With a strong 4.0 Glassdoor rating, our employees speak for themselves. We prioritize wellbeing, inclusivity, and a culture of respect at every level of the organization.
Invest in Your Growth: From continuous learning programs to structured career development pathways, we equip our team with the skills, tools, and opportunities needed to grow and lead in the age of AI.

Apply Now

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Module Lead — Fabric Data Engineering

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