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
- Perform data cleaning, processing, validation, and quality checks
- Develop SQL/PySpark code for ingestion, transformation, and analytical data preparation
- Assist in optimizing pipeline performance, storage efficiency, and compute consumption on Azure
- Contribute to documentation, technical design reviews, sprint activities, and engineering best practices
- Troubleshoot pipeline failures, data issues, and operational incidents
- Stay updated with Azure data engineering tools, cloud trends, and modern data architecture practices
This role is for you if you have the below
Educational qualifications
- 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
Preferred technical & functional skills
- Exposure to Azure Databricks, Fabric, or Spark-based data engineering
- Experience with Azure Functions or Logic Apps for data processing
- Familiarity with data lineage or Microsoft Purview
- Knowledge of building data quality rules or validation scripts
- Understanding of Power BI datasets, dataflows, or semantic models
- Basic understanding of Generative AI concepts, LLM data preparation, or Azure OpenAI integrations
