You will design and build ETL/ELT pipelines for structured and unstructured data, ensuring scalability and performance across systems.
Responsibilities
- Design and build ETL/ELT pipelines for structured and unstructured data.
- Develop and optimize data models for analytics and ML workflows.
- Support API integration and collaborate on lightweight services exposing data assets.
- Work with data scientists and ML engineers to productionize datasets and features.
- Ensure data quality, scalability, and performance across systems.
Required Skills
- 5+ years of experience in data engineering or backend development.
- Strong proficiency in Python and SQL.
- Experience with distributed systems including Spark, Kafka, and Airflow.
- Hands-on experience with cloud platforms (AWS preferred) and data lake/data warehouse design.
- Familiarity with APIs or event-driven architecture.
Preferred Skills
- Exposure to ML pipelines, feature stores, or AI platforms.
- Experience in financial services or regulated environments.
- Understanding of data governance and security best practices.