We are sharing a full-time opportunity for an experienced Data Engineer with strong expertise in Python, SQL, ETL pipelines, data modelling, exploratory data analysis, and scalable data-processing workflows to support research, analytics, and AI/ML initiatives.
The role focuses on transforming structured and unstructured information into reliable, production-quality datasets.
The successful candidate will build scalable data pipelines, improve data quality and validation, optimise SQL and processing workflows, and collaborate with researchers, data scientists, and engineers.
Key Responsibilities
- Data Pipelines & Processing: Design, build, and maintain scalable ETL pipelines
- Collect, clean, normalise, and transform structured and unstructured data
- Automate recurring processing workflows
- Monitor pipeline performance and troubleshoot failures
- Improve efficiency, scalability, and maintainability
- SQL, Databases & Data Modelling: Write and optimise SQL queries for 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
- Support scalable and reliable data-storage architectures
- Data Quality & Analysis: Conduct exploratory data analysis to identify patterns, anomalies, and quality issues
- Build automated validation and quality-control workflows
- Monitor accuracy, completeness, integrity, and consistency
- Investigate data issues and implement corrective actions
- Produce clear analytical summaries for technical stakeholders
- Python & AI/ML Data Support: Build processing workflows using Python, Pandas, and NumPy
- Develop reusable components for transformation and analysis
- Prepare datasets for AI and machine-learning initiatives
- Collaborate with researchers and data scientists on data requirements
- Support reliable training, evaluation, and experimentation workflows
Ideal Profile
- 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 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
- Familiarity with Jupyter Notebook, VS Code, PyCharm, or similar tools
- Exposure to AI/ML workflows is advantageous
- Familiarity with scikit-learn, Hugging Face Transformers, or AI APIs is beneficial
Engagement Details
- Full-time engagement
- Fully remote
- Compensation: $140,000–$180,000/year
- Work will involve Python, SQL, ETL, exploratory data analysis, database design, data modelling, validation, automation, and AI/ML dataset preparation
- Responsibilities may involve both structured and unstructured data
- Regular collaboration with researchers, data scientists, and engineering teams is expected
- Project scope, data sources, and technical requirements may evolve based on business and research needs
- Work must be completed without using confidential, proprietary, regulated, client-identifiable, restricted-access, or otherwise protected information belonging to any employer, client, research institution, data provider, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy