Junior Data Engineer / Junior Data Scientist

Job Description

Junior Data Engineer/Junior Data Scientist | edkey

The Tone:
This is a full-time, entry-level role at edkey, located in New York, NY. edkey is seeking to expand its IT team with an early-career data professional. This role is crucial for building and maintaining robust data pipelines, extracting valuable insights, and supporting analytics workflows within the organization. You will contribute directly to the foundation of data-driven decision-making.

The TL;DR
• Role: Early Career
• Type: Full-time
• Location: In-person, New York, NY
• Pay: $60000–$65000 yearly
• Team: IT Team, works with senior engineers
• Mission: Build and maintain data pipelines, extract insights, and support analytics workflows.
• Tech Stack: SQL, Python, Tableau, Power BI, Git, Linux command line, cloud basics

What You’ll Actually Do
• Data Management: Assist in the collection, cleaning, and transformation of data to prepare it for analytics and reporting.
• Query Development: Write and optimize SQL queries for efficient data extraction and manipulation tasks.
• Pipeline Support: Support the development and ongoing maintenance of data pipelines and associated databases.
• Insight Generation: Collaborate with senior team members to analyze datasets and generate actionable insights for various stakeholders.
• Documentation & Improvement: Document processes and data definitions, actively contributing to continuous improvement initiatives within the team.

The Must-Haves
• Background: Bachelor’s degree in Computer Science, Information Technology, or a related field; Entry-Level professional.
• Experience: Academic project experience with data analysis, database design, ETL, or similar data-related initiatives.
• Skills: Strong knowledge of SQL, understanding of data structures, algorithms, and relational databases, good problem-solving skills, attention to detail, and ability to learn quickly.
• Bonus: Familiarity with Python (or similar languages) for data manipulation, exposure to data visualization tools (Tableau, Power BI), basic understanding of data warehousing concepts and ETL processes, or experience with Git, Linux command line, or cloud basics.