Description : About the Role :
We are seeking an experienced Senior Data Engineer to design, develop, and optimize robust data ingestion and transformation pipelines using Azure Cloud services and GSK data platform tools. The ideal candidate will have strong technical expertise, a passion for building scalable data solutions, and the ability to lead engineering best practices across teams.
Key Responsibilities :
- Design, build, and maintain scalable data ingestion, egress, and transformation pipelines using Azure and GSK data platform tools.
- Optimize complex data engineering solutions using industry-standard design patterns and best practices.
- Deliver high-quality, production-ready data pipelines with automated testing, version control, and documentation.
- Implement and promote best practices in logging, data lineage, metadata management, and data quality.
- Collaborate closely with Data Platform teams, Solution Architects, and Engineering teams to deliver end-to-end solutions.
- Lead, mentor, and guide junior data engineers; support the adoption of Data Mesh principles.
- Ensure adherence to CI / CD, DevOps, QMS, and regulatory compliance standards.
Key Skills Required :
Strong hands-on expertise with Azure Data Services :
1. ADLS, ADF, Databricks, Synapse, Purview.
Proficiency in Python, Spark / PySpark, and modern data engineering frameworks.Strong understanding of ETL / ELT design, data modelling, data pipelines, and data quality practices.Experience with Kubernetes and GitOps tools (ArgoCD / FluxCD).Excellent communication, stakeholder management, and problem-solving abilities.Qualifications :
Bachelors or Masters degree in Computer Science, Information Technology, DataEngineering, or a related field.
Relevant certifications preferred (e.g., Azure Data Engineer Associate, Databricks Certified Data Engineer, or similar).Proven experience in delivering large-scale, cloud-based data engineering solutions.(ref : hirist.tech)