Data Engineer

Job Description Job Title: Junior Data Engineer Experience: 2–4 Years Location: Remote / Hybrid Notice Period: Immediate Joiner Job Summary We are looking for a motivated Junior Data Engineer with 2–4 years of experience to join our growing data engineering team. The ideal candidate should have hands-on experience in building and maintaining data pipelines, working with cloud-based data platforms, and developing scalable ETL/ELT solutions. You will collaborate with senior data engineers, data analysts, and business stakeholders to deliver reliable and efficient data solutions. Key Responsibilities Develop, maintain, and optimize ETL/ELT pipelines for data integration and processing. Build data processing applications using Python and PySpark . Ingest data from multiple sources, including APIs, databases, flat files, and streaming platforms. Write efficient, optimized, and scalable SQL queries for data transformation and reporting. Monitor, troubleshoot, and enhance the performance of existing data pipelines. Perform data quality validation and support data governance initiatives, including data lineage. Work with Azure Data Factory , Azure Data Lake , and Azure Databricks to develop cloud-native data solutions. Participate in Agile ceremonies, sprint planning, code reviews, and continuous improvement activities. Collaborate with cross-functional teams to understand business requirements and deliver data solutions. Required Qualifications Bachelor's degree in Computer Science , Information Technology, Engineering, or a related field. 2–4 years of hands-on experience in Data Engineering. Experience working with cloud platforms, preferably Microsoft Azure . Strong understanding of data integration, transformation, and pipeline development. Excellent SQL and analytical problem-solving skills. Good communication and collaboration skills. Ability to work independently as well as in a team-oriented Agile environment. Preferred Skills Exposure to streaming data processing frameworks. Understanding of data warehousing concepts. Knowledge of data governance and data quality practices. Familiarity with DevOps practices and deployment automation. Requirements Required Technical Skills Strong programming skills in Python Proficiency in SQL for querying and data transformation Hands-on experience with PySpark Experience with Azure Data Factory (ADF) Knowledge of Azure Data Lake Basic working knowledge of Azure Databricks Experience with Git version control Basic understanding of Apache Kafka Basic knowledge of CI/CD pipelines Good understanding of ETL/ELT architecture and best practices