Data Engineer

Roles & responsibilities

• Contribute to the development of data ingestion, transformation, and integration pipelines on Azure
• Support the implementation of ETL/ELT workflows using Azure Data Factory, Synapse, Databricks, and other Azure-native services
• Participate in building and maintaining data lakes, data warehouses, and analytical datasets
• Work with senior team members to understand client requirements and translate them into technical tasks

Educational Qualifications

• A bachelor's or master's degree in Engineering, Computer Science, or equivalent
• Relevant Azure Certifications (Azure Data Fundamentals(DP-900), Azure Fundamentals(AZ-900), Fabric Data Engineer Certificate (DP-700, preferred but not mandatory)

Work Experience

• 3-6 years of experience in data engineering, data integration, or cloud analytics
• Hands-on exposure to Azure data platform services and enterprise data engineering concepts

Mandatory Technical & Functional Skills

• Working experience with Azure Data Factory, Azure Data Lake Storage, Azure Databricks and Azure Synapse Analytics
• Good understanding of ETL/ELT concepts, data ingestion, and data transformation frameworks
• Proficiency in SQL and basic experience with PySpark or Python
• Experience working with structured and semi-structured data formats (Parquet, JSON, CSV, Avro)
• Understanding of data modeling concepts (dimensional modeling basics)
• Familiarity with CI/CD, Git repositories, and basic DevOps workflows
• Understanding of Azure security basics — RBAC, access control, networking fundamentals
• Experience working in an Agile environment, contributing to sprints, and collaborating with cross-functional teams
• Ability to communicate clearly and collaborate effectively with peers and senior team members