Jr. data engineer

Role Overview

We are looking for a Jr. data engineer to design and develop scalable data pipelines and manage cloud-based data architectures. You will work with large-scale data formats and ensure the quality, performance, and reliability of our data ecosystems.

Responsibilities

• Design and develop scalable data pipelines using Azure Data Factory (ADF) and equivalent AWS services.
• Work with Data Lakes, Lakehouse architectures, Delta Lake, and Data Warehouses across cloud platforms.
• Develop efficient data processing solutions using Apache Spark / PySpark.
• Build and maintain Semantic Models for analytics and reporting.
• Develop and optimize Advanced SQL queries, transformations, and data models.
• Work with large-scale formats such as Parquet and implement efficient storage and processing strategies.
• Apply Spark optimization techniques including partitioning, caching, broadcast joins, shuffle optimization, and query tuning.
• Work with cloud data services such as Azure Data Lake, Synapse, Fabric, S3, Glue, Athena, Redshift, and EMR.
• Ensure data quality, performance, scalability, security, and reliability of data pipelines.

Requirements

• 2–3 years of hands-on Data Engineering experience.
• Strong expertise in Azure Data Factory (ADF).
• Strong Advanced SQL skills.
• Good hands-on experience with Apache Spark / PySpark.
• Strong understanding of Data Lake, Lakehouse, Delta Lake, and Data Warehouse concepts.
• Good understanding of Parquet and columnar data formats.
• Experience with Semantic Models / Power BI datasets.
• Understanding of ETL/ELT, data modeling, partitioning, and Spark performance optimization.
• Good understanding of cloud-based data engineering architectures.
• 3 years of experience with Azure.

Skills

• Azure Data Factory
• Apache Spark
• PySpark
• SQL
• Delta Lake

Benefits

• Flexible schedule
• Provident Fund