LTI is looking for a mid to senior level Data Engineer to design, build and support modern data solutions across cloud and machine learning platforms, focusing on creating scalable data pipelines, enabling ML workflows and driving the development of reliable, high-quality data systems within Azure.
Requirements
- Strong experience working with Azure data services (ADF, Databricks, Synapse, Azure SQL, Azure Storage or similar)
- Proficiency in Python for data engineering and ML-related development
- Experience with machine learning frameworks such as scikit-learn, TensorFlow or PyTorch
- Hands-on background building ETL/ELT pipelines using Spark, Delta Lake or similar big-data tools
- Strong SQL skills including schema design, data modeling and performance tuning
- Solid understanding of version control, CI/CD practices and modern development workflows
- Experience supporting enterprise-scale environments or high-volume data systems
Responsibilities
- Build and maintain large-scale data pipelines that support analytics, reporting and machine learning initiatives
- Develop and optimize data workflows using Azure services such as Data Factory, Databricks, Functions and Azure Storage
- Collaborate with data scientists to enable feature engineering, prepare training datasets and support ML model deployment
- Integrate, cleanse and transform structured and unstructured data from a wide range of sources
- Design and implement scalable data models, schemas and storage patterns for batch and near-real-time processing
- Support ML/AI efforts using Python, Spark, MLflow, scikit-learn, TensorFlow or PyTorch
- Monitor pipeline performance, troubleshoot failures and ensure consistent data quality and reliability
Other
- Ability to work effectively within cross-functional engineering and analytics teams
- Strong analytical thinking, troubleshooting abilities and attention to detail
- 100% Remote for the right candidate
- background checks will be required
- Salary dependent upon experience
