Job Title

Key Responsibilities: 1. Develop, test, document, and maintain high-quality ETL/ELT pipelines using Snowflake and DBT. 2. Implement both full-load and incremental data ingestion patterns across multiple data sources. 3. Write clean, reusable, and scalable SQL and PySpark code to support data transformations and analytics workflows. 4. Participate in all phases of the software development lifecycle, including solution design, coding, testing, deployment, and optimization. 5. Diagnose, debug, and troubleshoot pipeline or code-related issues to ensure reliable data processing. Required Skills and Qualifications: 1. Minimum 2 years of professional experience as a Data Engineer or ETL Developer with demonstrable project experience. 2. Bachelor’s degree in Computer Science, Software Engineering, or a related field. 3. Strong proficiency in SQL, PySpark, and Python data libraries such as Pandas, NumPy, and SciPy. 4. Hands-on experience with Snowflake and good understanding of data warehousing concepts. 5. Experience working with AWS/Azure or another major cloud platform, with exposure to cloud-based data services. 6. Familiarity with agile methodologies, including sprint-based development practices. Additional Skills and Qualifications: 1. Exposure to big data technologies (e.g., Spark, Kafka, Hadoop). 2. Understanding of data science and machine learning concepts, tools, and workflows.