Job Description

Job Summary

We are looking for an experienced Senior Data Engineer with 7+ years of hands-on experience in designing, developing, and maintaining scalable, cloud-based data engineering solutions. The ideal candidate should have strong expertise in Snowflake, Python/PySpark, SQL, and modern ETL/ELT frameworks, with a proven ability to build reliable, high-performance data pipelines supporting enterprise analytics, reporting, and AI/ML initiatives.

Key Responsibilities

Design, develop, and maintain scalable, high-performance data pipelines and cloud-based data platforms.
Build and optimize batch and near-real-time data ingestion and transformation frameworks from multiple source systems.
Develop and maintain ETL/ELT pipelines using Snowflake, Python/PySpark, and SQL.
Implement Snowflake features such as Streams, Tasks, Snowpipe, Dynamic Tables, and Snowpark for efficient data processing.
Develop incremental data processing and Change Data Capture (CDC) solutions.
Design and implement data quality, reconciliation, validation, monitoring, and observability frameworks.
Optimize SQL queries, data models, and processing workflows for performance, scalability, and cost efficiency.
Support data preparation and feature engineering for advanced analytics and machine learning workloads.
Ensure compliance with enterprise data governance, security, privacy, and regulatory standards.
Troubleshoot complex data integration, data pipeline, and performance-related issues.
Collaborate with Product Managers, Business Stakeholders, and Solution Architects to translate business requirements into technical solutions.
Participate in architecture reviews, technical design discussions, and continuous improvement initiatives.
Follow CI/CD, version control, automated deployment, and Agile development practices.
Work effectively with globally distributed teams and cross-functional stakeholders.

Technical Skills and Experience