Job Description

Job Overview:

We are seeking a seasoned Data Engineer with 6 8+ years of experience to support critical data initiatives and drive the development of scalable, high-performance data solutions. This role is ideal for someone with deep technical expertise in data pipeline engineering, Snowflake optimization, and secure data architecture.

Key Responsibilities:

• Design, build, and maintain scalable and efficient data pipelines.
• Develop and manage data warehouses and data lakes for analytics and machine learning use cases.
• Ensure data quality, integrity, and adherence to best practices.
• Optimize data storage, access, and retrieval for performance and cost-efficiency.
• Monitor and tune Snowflake environments for performance and credit usage.
• Implement secure data sharing, row-level access policies, and data masking for sensitive information (e.g., PII, financial data).
• Enforce robust role-based access controls (RBAC) within Snowflake.
• Collaborate with data scientists, analysts, and cross-functional teams to support business goals.
• Create semantic layers, aggregate tables, and governed data models (Star/Snowflake schemas) to enable scalable, business-friendly analytics.

Required Qualifications:

• 6 8+ years of hands-on experience in data engineering.
• Strong expertise in SQL and scripting languages.
• Proven experience with scalable ETL pipelines and scheduler tools.
• Experience with CI/CD orchestration and automation (e.g., Jenkins, GitHub).
• Deep knowledge of Snowflake, including performance tuning and secure data sharing.
• Ability to build semantic data models and design analytics architectures.

Preferred Qualifications:

• Experience with Machine Learning, LLMs, or AI model development/deployment.
• Strong written and verbal communication skills for cross-team collaboration.

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