Remote Position: Data Engineer

Jobgether

1d • Remote

About The Position

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineer. In this role, you will play a crucial part in transforming legacy systems into cloud-native architectures, facilitating the extraction, transformation, and loading (ETL) of complex data from various sources. Your expertise in Python and AWS will support the design and implementation of robust solutions that enable comprehensive data analysis and reporting. The impact of your work will be seen across various analytics and decision-making processes, making this role critical for our partner’s operations. Given the evolution of data demands, your contributions will help set new standards in data management and accessibility.

Requirements

• 5+ years of experience as a Data Engineer, Data Scientist, or Backend Software Engineer.
• Bachelor’s degree in computer science, statistics, mathematics, economics, or related field.
• Strong skills in Python and SQL, with proficiency in other data engineering languages (e.g., R, SAS, Scala).
• Experience handling large-scale data projects involving data integration, cleaning, ETL, and reporting.
• Experience developing and implementing data reliability, efficiency, and quality checks.
• Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda) to build data solutions in a cloud-native environment.
• Familiarity with various database systems including Oracle, PostgreSQL, MySQL, and MongoDB.

Responsibilities

• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions.
• Develop efficient data processing and transformation workflows to support analytics and reporting needs.
• Design, build, and maintain data pipelines and automated ETL processes using tools like Python, R, and Jupyter Notebooks.
• Integrate disparate structured and unstructured data from APIs, databases, and cloud storage into unified datasets.
• Implement processes for data cleaning, transformation, and validation to ensure data accuracy and compliance with security policies.
• Develop dashboards and visualizations to support operational decision-making.
• Provide full lifecycle assistance in deploying, optimizing, and maintaining complex code with data processing routines.

Benefits

• Medical, Vision, and Dental Insurance.
• 401(k) Savings Plan.
• Flexible Spending Accounts (FSA).
• Education and Professional Training.
• Paid Time Off (PTO).
• Employee Assistance and Identity Theft Protection.
• Employee Referral and Merit Recognition Programs.
• Paid Holidays: 11 per year.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level