Position: Data Engineer with Snowflake and Python Experience
Location: New York , NY fully onsite - Face to Face interview is required
Duration: 6 months and ext based on the business needs
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines using Snowflake as the primary data warehouse.
• Write efficient Python scripts for ETL/ELT processes, automation, and data transformation.
• Collaborate with business analysts, data scientists, and stakeholders to understand data requirements.
• Optimize queries, manage schemas, and ensure high performance of Snowflake environments.
• Implement data quality checks, validation frameworks, and monitoring solutions.
• Integrate data from multiple sources (APIs, databases, cloud storage) into Snowflake.
• Ensure compliance with data governance, security, and privacy standards.
• Document workflows, processes, and best practices for team knowledge sharing.
Required Skills & Qualifications:
• Strong hands‑on experience with Snowflake (data modeling, query optimization, warehouse management).
• Proficiency in Python for data engineering tasks (Pandas, SQL Alchemy, PySpark optional).
• Solid understanding of SQL and relational database concepts.
• Experience with ETL/ELT tools (e.g., Airflow, dbt, Informatica, Talend).
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform) and their data services.
• Knowledge of CI/CD pipelines and version control (Git).
• Excellent problem‑solving skills and ability to work in cross‑functional teams.
Preferred Qualifications:
• Bachelor’s or Master’s in Computer Science, Information Technology, or related field.
• Experience with data lakes, big data frameworks (Spark, Hadoop).
• Exposure to API integrations and real‑time data streaming (Kafka, Kinesis).
• Strong communication skills to translate technical concepts into business insights.
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