Role & responsibilities

About the Role

We are looking for a skilled Data Engineer who can design and maintain robust data pipelines, work with large-scale structured and semi-structured pharma datasets, and collaborate closely with Data Scientists and Python Developers to deliver clean, validated, production-grade data infrastructure.

Pipeline Design & Development

- Design and build scalable ETL/ELT pipelines for ingesting, transforming, and loading pharmaceutical data from multiple sources
- Process indication-level market forecast data from Excel workbooks into structured JSON and DB-ready formats for frontend visualisation
- Build and maintain data extraction pipelines from clinical trial registries, conference abstracts, and drug databases
- Implement multi-step validation workflows to ensure pipeline output accuracy and completeness before downstream handoff

Data Modelling & Architecture

- Design normalised relational schemas in SQL Server to support pharmaceutical analytics use cases
- Collaborate with Data Scientists on data preparation and feature engineering pipelines
- Maintain data dictionaries, schema documentation, and lineage records for all active pipelines
- Contribute to architecture decisions on data storage, processing strategies, and API integrations

Quality, Validation & Reliability





- Own data quality across assigned pipelines implement automated checks, alerting, and audit trails
- Investigate and resolve silent data errors including missing fields, incorrect labels, zero-value nodes, and schema mismatches
- Write thorough unit and integration tests for all pipeline components

Collaboration & Standards

- Work within an agile delivery framework participate in sprint planning, estimation, reviews, and retrospectives
- Follow and contribute to team-wide GitHub standards: branching strategy, PR reviews, naming conventions, and documentation
- Actively use AI coding tools (GitHub Copilot, Claude, etc.) as part of everyday development
- Produce explicit technical documentation and handoff notes for every delivery

Preferred candidate profile

- Python (3+ years, production pipelines)
- SQL Server (primary)
- SQL complex queries, stored procedures, optimisation
- Git / GitHub (branching, PRs, code review)
- ETL/ELT design and implementation
- Pandas, SQLAlchemy, Pydantic
- Data modelling and schema design
- Excel / openpyxl for source data handling
- REST API integration and data extraction
- Docker or containerised environments (desirable)
- Data validation and testing practices
- Selenium / web scraping tools (desirable)
- JSON / XML data processing
- Airflow or equivalent orchestration (desirable)

📌 Data Engineer (Hyderabad)
🏢 GlobalData
📍 Hyderabad