Data Engineer

Overview

An experienced Data Engineer is sought to support a growing Data & Analytics function. The role focuses on the design, development, and maintenance of scalable data infrastructure, including pipelines, stored procedures, and automation scripts. This opportunity is ideal for candidates with a strong foundation in SQL and Python, and familiarity with modern data warehousing and reporting tools.

Onsite 2x per week (hybrid) in Midtown NYC

Data Integration & Transformation:

• Build and maintain data pipelines to extract, load, and transform data from multiple sources.
• Develop, optimize, and manage SQL Server stored procedures, queries, and views.

Automation & Scripting:

• Write and maintain Python scripts for automation, data transformation, and reporting processes.

Data Quality & Management:

• Ensure the consistency, integrity, and reliability of data across systems.
• Collaborate with stakeholders to validate and interpret data for business use.

Platform Support:

• Assist with data warehouse development and performance tuning within Snowflake.

Documentation & Standards:

• Create and maintain technical documentation for data workflows, structures, and processes.

• Minimum 5 years of experience in a Data Engineering role.
• Proficiency in SQL, including complex queries and stored procedure development in SQL Server.
• Practical experience in Python for data processing and automation.
• Understanding of ETL/ELT processes and data modeling principles.
• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or equivalent experience.

• Exposure to business intelligence platforms such as Tableau.
• Experience working with Git or other version control systems.
• Familiarity with cloud environments like AWS, Azure, or GCP.
• Understanding or prior experience with AI/ML projects or frameworks.
• Awareness of data governance principles and documentation standards.

This position offers the opportunity to contribute to a dynamic data infrastructure in a collaborative environment focused on continuous improvement and innovation in data practices.

• Full-time

• Associate