Associate, Data Engineering

The Associate, Data Engineering supports the architecture, pipelines, and code behind Evergreen’s enterprise data systems, including financial and media data. This junior, hands-on role builds and maintains the infrastructure that teams across the company rely on for reporting, integrations, and platform requests. The ideal candidate has practical ETL experience, is comfortable using SQL and Python, and is eager to build greater ownership of data architecture over time., * Support and maintain data pipelines for Evergreen’s enterprise systems, including financial, media, and operational applications.

• Build and maintain data ingestion pathways using APIs, S3, direct warehouse data shares, and webhooks.
• Translate stakeholder integration requests into technical requirements and maintained data connections.
• Develop and maintain ETL/ELT pipelines that deliver consumable data into Snowflake.
• Write and test SQL and Python transformations, participate in code reviews, and follow documentation practices.
• Troubleshoot pipeline failures, performance issues, and data quality concerns.
• Support schema design, table maintenance, performance optimization, validation checks, and appropriate access controls.
• Maintain documentation of data architecture, schemas, pipelines, and integration points.

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.
• 0-2 years of experience in data engineering, software engineering, or a related technical field; internships and relevant coursework count.
• Proficiency in SQL and Python.
• Hands-on experience building or supporting ETL/ELT pipelines.
• Experience working with data ingestion and integration methods, including APIs, S3, direct warehouse data shares, and webhooks.
• Ability to work appropriately with sensitive and financial data under defined access controls.

Preferred:

• Exposure to Snowflake or another cloud data warehouse.
• Familiarity with AWS or other cloud infrastructure.

Core Competencies

• Curiosity and a desire to understand how systems and processes work.
• Sound judgment and a willingness to challenge the status quo when improvements are needed.
• Strong collaboration and communication skills.
• Attention to detail and a commitment to reliable, high-quality work.
• Ability to learn quickly and take on increasing responsibility over time.

Salary: $65,000 - $75,000

The above represents the expected base salary range for this role.

Why Work with Us

Since our founding in 2009, Evergreen Trading has always believed that our people are the most valuable part of our business. That’s why our company is 100% employee owned. It’s also why we continue to invest in our employees’ professional and personal development through company-sponsored training, mentorship, and a dedication to DEIB. Other highlights include:

• Automatic enrollment in the Employee Stock Ownership Plan (“ESOP”)
• 401(k) plan with an employer match
• Extensive benefits offering in which Evergreen covers up to 75% of health premiums for employee and dependent coverage
• Generous time off including office closure between Christmas and New Year’s Day
• Hybrid work schedule

About Evergreen

At Evergreen Trading, we’re driven by collaboration and value creation for our clients. That’s why we’re the go-to, strategic partner for marquee brands across industries. Headquartered in NYC, we’re a media investment and trade firm that helps brands achieve their goals by leveraging their unwanted assets to purchase media. Our unique approach allows clients to improve their ROI by turning excess inventory, equipment, real estate, and more into media purchasing power. If you’re looking for a dynamic work environment and have a passion for doing things differently, Evergreen Trading is the place for you., The Data & Analytics team builds and supports the data infrastructure, systems, and integrations that power Evergreen’s financial, media, and business operations. The team partners across the organization to ensure data is accessible, reliable, secure, and ready to support reporting, decision-making, and operational needs.