Remote | Data Engineer — $140,000–$180,000/year
About The Position
This is a full-time, fully remote opportunity for an experienced Data Engineer supporting research, analytics, and AI/ML initiatives. The role transforms structured and unstructured information into reliable, production-quality datasets by building scalable data pipelines, improving data quality and validation, and optimizing SQL and processing workflows. The engineer will collaborate regularly with researchers, data scientists, and engineering teams. Project scope, data sources, and technical requirements may evolve based on business and research needs. Work must not use confidential, proprietary, regulated, client-identifiable, restricted-access, or otherwise protected information belonging to an employer, client, research institution, data provider, or other third party. The opportunity is available through 24-MAG LLC, which connects experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. Applicants’ information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with its Privacy Policy.
Requirements
- Strong proficiency in Python and SQL.
- Hands-on experience designing and maintaining ETL pipelines.
- Experience with exploratory data analysis.
- Proficiency with Pandas and NumPy.
- Experience with PostgreSQL, MySQL, or comparable relational databases.
- Strong understanding of data modelling and database schemas.
- Experience working with structured and unstructured datasets.
- Strong focus on data quality, integrity, and reliability.
- Strong analytical and problem-solving skills.
- Experience collaborating with researchers, data scientists, or engineering teams.
Nice To Haves
- Familiarity with Jupyter Notebook, VS Code, PyCharm, or similar tools.
- Exposure to AI/ML workflows.
- Familiarity with scikit-learn, Hugging Face Transformers, or AI APIs.
Responsibilities
- Design, build, and maintain scalable ETL pipelines.
- Collect, clean, normalize, and transform structured and unstructured data.
- Automate recurring data-processing workflows.
- Monitor pipeline performance, troubleshoot failures, and improve efficiency, scalability, and maintainability.
- Write and optimize SQL queries for data extraction and transformation.
- Work with relational databases such as PostgreSQL and MySQL; design and maintain schemas and data models; improve query performance and data-access patterns; and support scalable, reliable data-storage architectures.
- Conduct exploratory data analysis to identify patterns, anomalies, and data-quality issues.
- Build automated validation and quality-control workflows and monitor data accuracy, completeness, integrity, and consistency.
- Investigate data issues and implement corrective actions.
- Produce clear analytical summaries for technical stakeholders.
- Build Python processing workflows and reusable components for transformation and analysis using tools such as Pandas and NumPy.
- Prepare datasets for AI and machine-learning initiatives.
- Collaborate with researchers and data scientists on data requirements and support reliable training, evaluation, and experimentation workflows.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
