Associate Data Engineer (Fresher)

Job Title: Associate Data Engineer (Fresher)

Job Summary: We are seeking motivated freshers to join our team as Associate Data Engineers. This role offers an opportunity to build and maintain data pipelines, data warehouses and analytics platforms on the Microsoft data stack. The ideal candidate will have a strong foundation in SQL, a clear understanding of data warehouse and ETL concepts, and a keen interest in working with tools such as SQL Server, Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric and Power BI.

Key Responsibilities:

Build, test and maintain ETL/ELT pipelines using Azure Data Factory, SSIS or Microsoft Fabric Data Pipelines to ingest data from multiple source systems.

Develop and maintain data warehouse and lakehouse structures, including fact and dimension tables, star/snowflake schemas and staging layers.

Write, optimize and maintain SQL queries, views, stored procedures and transformation scripts.

Implement data quality checks, validation rules and error handling to ensure accurate and reliable data.

Monitor scheduled pipelines and jobs, troubleshoot failures and support performance tuning.

Prepare curated, analysis-ready datasets and semantic models for reporting in Power BI.

Work with data stored in Azure SQL Database, Azure Data Lake Storage, Azure Synapse Analytics or Fabric OneLake.

Translate business and reporting requirements into data models and pipeline designs under the guidance of senior engineers.

Document data sources, data flows, data models and transformation logic.

Collaborate with data analysts, BI developers and business users to deliver data solutions on time.

Continuously learn and stay current with Microsoft data platform features and data engineering best practices.

Required Qualifications:

Bachelors degree in Computer Science, Information Technology, Engineering, Mathematics or a related field (2025 / 2026 graduates eligible).

Strong working knowledge of SQL joins, subqueries, aggregations, window functions, CTEs, stored procedures and basic query optimization.

Understanding of data warehouse concepts OLTP vs OLAP, dimensional modeling, star and snowflake schemas, fact and dimension tables, slowly changing dimensions.

Understanding of ETL/ELT processes, data integration and incremental data loading.

Familiarity with the Microsoft data stack SQL Server and at least one of Azure Data Factory, SSIS, Azure Synapse Analytics or Microsoft Fabric.

Basic programming knowledge in Python (or PySpark) for data processing.

Hands on experience through academic projects, internships or self-learning in building a data pipeline or data warehouse.

Strong analytical, logical reasoning and problem solving skills.

Good verbal and written communication skills.

Eagerness to learn, attention to detail and the ability to work well in a team.

Preferred Qualifications:

Microsoft certifications such as DP-900 (Azure Data Fundamentals), DP-700 (Fabric Data Engineer Associate), DP-600 (Fabric Analytics Engineer Associate) or PL-300 (Power BI Data Analyst Associate).

Exposure to Apache Spark, Azure Databricks or Fabric notebooks.

Familiarity with Delta Lake and the medallion (bronze/silver/gold) architecture.

Basic knowledge of Power BI, DAX and Power Query for validating and consuming data models. Understanding of cloud fundamentals on Microsoft Azure (storage, compute, security and access control).

Familiarity with version control (Git), CI/CD concepts and Agile w

ays of working.

Academic projects, internships or portfolio work in data engineering, BI or data warehousing.