Role Description

• Design, develop, and maintain scalable data pipelines.
• Build and optimize ETL/ELT workflows.
• Develop and manage data warehouses and data lakes.
• Integrate data from multiple sources.
• Optimize database performance and data quality.
• Collaborate with data scientists, analysts, and application teams.
• Implement data governance and security best practices.
• Monitor and troubleshoot data pipeline issues.
• Automate data processing workflows.
• Maintain technical documentation.

Requirement

• 8+ years of Data Engineering experience.
• Strong SQL and Python programming skills.
• Experience with Spark and ETL frameworks.
• Hands-on experience with cloud data platforms.
• Knowledge of data warehousing concepts.
• Experience with workflow orchestration tools.
• Understanding of data modeling and optimization.
• Familiarity with Agile methodologies.

NiceToHave

• Python, SQL, Scala
• Apache Spark, Hadoop, Kafka
• ETL/ELT Development
• Data Warehousing
• Snowflake, Redshift, BigQuery
• AWS, Azure, Google Cloud Platform
• Airflow, Databricks
• SQL Server, PostgreSQL, MySQL
• Git, Docker, Kubernetes
• Data Engineering
• ETL/ELT Development
• Data Warehousing
• Cloud Platforms
• Big Data Technologies
• Database Management
• Performance Optimization
• Data Modeling