About The Opportunity
Opportunity in the Cloud Data & Analytics sector delivering enterprise-scale, production-grade data platforms and analytics solutions for customers across industries. This role focuses on building scalable, secure Azure-based data engineering pipelines and analytics-ready data lakes to enable real-time insights and ML workloads.
Role: Azure Data Engineer (On-site, India)
Role & Responsibilities
- Design, build, and operate end-to-end data pipelines using Azure Data Factory and Azure Databricks to support ETL/ELT workloads.
- Develop PySpark and Python data processing jobs for batch and near-real-time ingestion, transformation, and enrichment of large datasets.
- Implement and optimize data models and queries in Azure Synapse and SQL to meet SLAs for performance and cost-efficiency.
- Architect and manage scalable data lake storage on Azure Data Lake (Gen2), applying best practices for partitioning, format (Parquet/Delta), and data governance.
- Build CI/CD pipelines and infrastructure-as-code patterns with Azure DevOps to automate deployments, testing, and environment promotion.
- Monitor pipeline health, troubleshoot data quality issues, implement observability and alerting, and collaborate with data scientists and BI teams to ship production solutions.
Skills & Qualifications
Must-Have
- Azure Data Factory
- Azure Databricks
- PySpark
- SQL
- Azure Synapse Analytics
- Azure Data Lake
- Python
- Azure DevOps
Preferred
- Delta Lake
- Terraform
- Apache Kafka
Additional Qualifications
- 3+ years of hands-on experience in cloud data engineering (Azure preferred) or equivalent demonstrable experience.
- Experience delivering production ETL/ELT solutions, data modeling for analytics, and collaborating with data science/BI teams.
- Microsoft certification such as Microsoft Certified: Azure Data Engineer Associate is a plus.
Benefits & Culture Highlights
- On-site, collaborative engineering environment with strong focus on upskilling and technical mentorship.
- Work on high-impact enterprise data platforms and exposure to ML/analytics use-cases.
- Competitive compensation, training support, and clear career progression for data engineers.
To apply, please ensure your CV highlights hands-on Azure Data Factory and Databricks experience, PySpark development, and examples of production data pipelines or Synapse/SQL performance tuning.
Skills: azure databricks,azure data engineer,sql,python
