Data Engineer

Job Description

This role is for one of Zepcruit's clients. Job Description: Junior Data Engineer Location: Baner, Pune, Maharashtra. Experience: 1?3 years Type: Full-Time About The Role: We are seeking a motivated Junior Data Engineer to support our data engineering initiatives. You will work closely with senior engineers to design, build, and maintain scalable data pipelines on Azure. This role is ideal for someone who wants to grow into a senior/lead data engineering position in the future. Key Responsibilities: - Assist in building and maintaining ETL/ELT pipelines using Azure Data Factory. Develop, optimize, and test data transformation workflows using Azure Databricks (PySpark/SQL). Work with stakeholders to understand data needs and support analytical and reporting requirements. Support senior engineers in designing scalable and secure data architectures. Perform data validation, quality checks, and ensure clean and reliable data flow. Monitor, troubleshoot, and optimize data pipelines for performance and cost. Collaborate with data analysts, data scientists, and other engineering teams. Required Skills & Experience: - 1?3 years of experience as a Data Engineer or in a similar data-focused role. Mandatory: Hands-on experience with Azure Databricks (PySpark, Delta Lake). Strong knowledge of Azure Data Factory (pipelines, triggers, activities). Good understanding of SQL (optimization, joins, data modeling basics). Familiarity with Azure storage solutions (ADLS Gen2, Blob Storage). Basic understanding of CI/CD concepts and version control (Git). Strong problem-solving skills and willingness to learn. Good to Have: - Exposure to Azure Synapse, Azure Functions, or Event Hub/Kafka. Experience working with structured and unstructured datasets. Knowledge of Python for scripting. Understanding of data warehousing concepts (Star/Snowflake schema). Why Join Us: - Opportunity to work with experienced data engineers and grow quickly in your career. Work on modern data platforms and cutting-edge Azure technologies. Supportive environment focused on learning, ownership, and innovation. Chance to contribute meaningfully to end-to-end data engineering projects.