About the job

• Key ResponsibilitiesDesign, develop, and maintain ETL/ELT data pipelines.
• Extract, transform, and load data from multiple sources.
• Build and optimize data warehouses, data lakes, and databases.
• Write complex SQL queries and develop data transformation scripts using Python.
• Work with big data technologies such as Apache Spark and Hadoop.
• Implement data quality checks, validation, and monitoring.
• Optimize pipeline performance, reliability, and scalability.
• Collaborate with data analysts, data scientists, and business teams.
• Ensure data security, governance, and compliance.
• Troubleshoot data pipeline failures and resolve data-related issues.
• Required SkillsProgramming: Python, SQL
• Databases: MySQL, PostgreSQL, SQL Server
• ETL Tools: Informatica, Talend, or dbt
• Big Data: Apache Spark, Hadoop, Kafka
• Cloud Platforms: AWS, Azure, or Google Cloud Platform
• Data Warehousing: Snowflake, Amazon Redshift, or Google BigQuery
• Workflow Orchestration: Apache Airflow
• Version Control: Git and GitHub
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