Design, develop, and maintain robust ETL/ELT pipelines (SQL, Python) with large datasets
Build scalable data workflows with Spark, PySpark, and cloud platforms
Translate business requirements into well-structured analytics datasets
Apply data modeling principles for analytics-ready data
Optimize pipelines for performance, reliability, and cost
Ensure data quality, validation, and monitoring across pipelines

🎯 Requirements

5+ years of experience in data engineering or ETL development
Strong proficiency in SQL and Python with production-grade ETL pipelines
Hands-on experience with Databricks, Spark, and PySpark
Experience with cloud data platforms (AWS, Azure, GCP)
Strong understanding of data warehousing concepts and dimensional modeling
Experience building batch and incremental data pipelines

🎁 Benefits

Generous time off policies
Top shelf benefits
Education, wellness and lifestyle support

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