DE (SQL+Python+Data Pipeline) Professional

Role Overview: We are looking for a Junior Data Engineer with a strong foundation in SQL, databases, and cloud data platforms . This role is ideal for candidates who have hands-on experience in querying large datasets, working with data frames in Python, and are eager to grow in a data engineering environment involving cloud technologies, data pipelines, and real-time data streaming. Key Responsibilities: Write, optimize , and maintain complex SQL queries for data extraction, transformation, and reporting. Work with relational databases and cloud data warehouses such as Snowflake and Redshift . Apply data modeling principles , including normalization and understanding of various data types. Utilize Python along with Pandas or PySpark for data processing and analysis. Assist in the development and maintenance of ETL/ELT pipelines to manage large-scale data workflows. Collaborate with analysts, engineers, and business teams to ensure clean, consistent, and accessible data. Gain exposure to NoSQL databases such as MongoDB or DynamoDB. Use cloud platforms , preferably AWS , for managing and accessing data services. Create reports and dashboards using visualization tools like Tableau, Power BI, or Looker. Support initiatives involving real-time data streaming and help manage data streaming platforms (e.g., Kafka, Kinesis). Required Skills : 1+ years of experience working with SQL and databases. Strong proficiency in SQL and understanding of data modeling and data warehousing concepts . Basic experience with Python and data frame libraries like Pandas or PySpark . Familiarity with cloud-based data warehouse platforms like Snowflake and Redshift . Understanding of NoSQL databases and unstructured data handling. Exposure to ETL/ELT tools and practices . Awareness of cloud platforms , especially AWS and its data services. Working knowledge of data visualization tools such as Tableau, Power BI, or Looker. Interest in or basic understanding of real-time data streaming platforms .