Data Engineer

1 day ago

Bangalore, India One Tapp Consulting Full time

Location - Bengaluru Experience : 2+ years Key Responsibilities: * Design and Development: Design, build, and maintain robust, scalable, and optimized ETL/ELT data pipelines using Python and standard data warehousing principles. * Data Platform Management: Implement and manage data processing jobs and workflows within the Databricks platform, leveraging Spark (PySpark) for large-scale data transformation. * Data Modeling and Querying: Develop complex and efficient SQL queries, stored procedures, and optimize database performance; contribute to the design and implementation of dimensional and relational data models. * Code Quality and Automation: Ensure high standards of code quality, testing, and documentation; implement CI/CD practices and automation for data workflows. * Collaboration: Work closely with Data Scientists, Analysts, and other software engineers to understand data requirements and deliver solutions that meet business needs. * Monitoring and Optimization: Monitor data pipeline performance, troubleshoot issues, and implement necessary optimizations to ensure data accuracy and timely delivery. Required Qualifications * Experience: Minimum of 2 years of professional experience in a Data Engineering, BI Engineering, or similar role. Technical Expertise (Must-Haves): * Expert proficiency in writing complex, optimized SQL queries and experience with various relational databases (e.g., PostgreSQL, SQL Server, MySQL). * Expert proficiency in Python for data manipulation, scripting, and pipeline development (experience with libraries like Pandas, NumPy is a plus). * Demonstrated experience and strong working knowledge of the Databricks platform, including Delta Lake, Spark (PySpark), and notebook-based development. * Data Concepts: Solid understanding of data warehousing concepts, data modeling (e.g., Star Schema, Snowflake Schema), and ETL/ELT processes. * Communication: Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.

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