About the Role

Campus Activewear is scaling a cloud data platform that consolidates multi-department data into a reliable lakehouse for analysis and decision-making.

We need a hands-on Full-Stack Data Engineer who can own the data pipeline layer end-to-end, partner with IT (who own infrastructure), reverse-engineer and stabilize existing vendor-built work, and also build Azure-hosted web applications on top of trusted data.

This is not a prompt AI and ship notebooks” role. You must be able to design, debug, document, and operate production pipelines yourself.

What You Will Own:

Data platform (primary)

- Stabilize, document, and improve existing Azure Data Factory ADLS Databricks (bronze / silver / gold) pipelines
- Onboard recent source systems into the medallion architecture
- Improve gold-layer reliability (especially consolidated sales / channel registers)
- Own failed-pipeline triage and on-call for production breaks
- Work with IT on infra (networking, VMs/SHIR, access, secrets) while owning pipeline logic, data quality, and delivery
- Take over / reverse-engineer vendor-delivered ADF pipelines and Databricks notebooks

Web applications (secondary but real)

- Build internal tools on Azure App Service — dashboards, workflows, data-entry portals, and APIs over gold tables
- Stack is open (Python/FastAPI, React/Next, .NET, etc.) — choose pragmatically for Campus needs

Business partnership

- Translate Sales / ops / channel requirements into data models and usable apps




- Balance stakeholder communication with deep engineering delivery

Must-Have Skills

- Strong fundamentals in ETL/ELT, lakehouse / medallion patterns, SQL, and Python
- Hands-on experience with at least one cloud data stack at production scale — prefer Azure + Databricks (ADF, ADLS/Delta, notebooks/jobs); also strong: Synapse/Fabric, Snowflake + orchestration, AWS Glue/EMR + S3 if ramp to Azure/Databricks is fast
- Can explain a past pipeline source landing clean curated consumer without relying on AI-generated answers
- Comfort with production operations: retries, monitoring, failure diagnosis, incremental loads / MERGE concepts, data quality checks
- Ability to build and deploy simple-to-moderate web apps / APIs on Azure
- Clear documentation habits (runbooks, pipeline maps, data contracts)

Strong Preference

- Retail / CPG / footwear / multi-channel sales domain
- SAP extraction / connectors / sales data familiarity
- Unity Catalog, Delta Lake, service principals / Key Vault (or equivalent elsewhere)
- Experience inheriting messy vendor codebases and making them operable

What We Are Not Looking For

- Pure Power BI / analyst profiles with light “data eng” exposure
- Candidates who can only describe architecture slides, not debug a failed run
- Frontend-only or backend-only engineers with no data pipeline experience
- People who need a large data team around them to be effective

📌 Full-Stack Data Engineer (Gurugram)
🏢 Campus Activewear
📍 Gurugram