Description

You design and maintain end-to-end data models and ETL/ELT pipelines on Azure, owning the lifecycle from ingestion to analytics-ready storage.

This role is on-site.

Responsibilities

• Design and maintain conceptual, logical, and physical data models, including dimensional models for analytics.
• Build and optimize end-to-end ETL/ELT pipelines using Azure Data Factory and Azure Databricks.
• Ingest data from SQL/NoSQL databases, APIs, flat files, and cloud storage with incremental loads and robust error handling.
• Optimize Spark jobs for performance, scalability, and cost efficiency within Azure Data Lake (ADLS Gen2).
• Implement data quality checks, validation rules, and reconciliation processes to ensure integrity and compliance.

Required Skills

• 13+ years of experience in data engineering roles.
• Strong proficiency in SQL and database design principles.
• Hands-on experience with Azure Data Factory for pipeline orchestration.
• Expertise in Azure Databricks and Spark for data processing and optimization.
• Proven track record developing ETL/ELT pipelines from multiple sources.
• Experience integrating with APIs and managing flat file ingestion.
• Understanding of data governance, security, and lineage documentation.

Preferred Skills

• Experience collaborating with solution architects on data platform architecture.

Key Skills

Education

Any Gradute