Senior Data Engineer

• Design, develop, and maintain enterprise-scale data pipelines in Snowflake.
• Implement and manage data ingestion frameworks using Fivetran.
• Develop ETL/ELT workflows using Dbt, AWS Glue and PySpark.
• Build and optimize data lake solutions on AWS/Snowflake.
• Perform source-to-target mapping and support data migration initiatives.
• Implement data quality, validation, reconciliation, and monitoring frameworks.
• Develop reusable pipeline patterns and automation frameworks.
• Collaborate with architects, business stakeholders, and analytics teams to deliver trusted data products.
• Support AI and GenAI use cases by preparing and managing high-quality datasets.
• Follow DataOps, CI/CD, governance, and security best practices.

Required Technical Skills:

• Core Technologies
• Snowflake
• Fivetran
• DBT
• AWS Glue
• Python
• SQL
• PySpark

Data Engineering:

• ETL / ELT Development
• Data Warehousing
• Data Lake Architecture
• Source-to-Target Mapping
• Data Quality Frameworks
• Pipeline Automation
• Performance Optimization

DevOps / DataOps:

• Git
• CI/CD Pipelines
• Agile Delivery

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• 10 days ago

• We are seeking a highly skilled Senior Data Engineer with expertise in Fivetran, Snowflake, Dbt, AWS Glue, Python, SQL, and cloud-native data engineering.
• The ideal candidate will be responsible for building scalable data ingestion and transformation frameworks, enabling analytics, data products, and AI-driven initiatives across the enterprise.
• 7 10 years of overall experience in Data Engineering and Data Integration.

• $100,000-140,000 per year, + $140,000-230,000 per year