Data Engineer

hiring a Data Engineer to support a Generative AI platform by building scalable data pipelines and systems. This role blends traditional data engineering with modern development practices, including exposure to APIs and microservices for AI/ML integration.
Hybrid Schedule: In-office 3 days per week

Key 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.

Must-Have:

• 5+ years of experience in data engineering or backend development.
• Strong in Python, SQL, and distributed systems (e.g., Spark, Kafka, Airflow).
• Experience with cloud platforms (AWS preferred) and data lake/data warehouse design.
• Familiarity with APIs or event-driven architecture is a plus.

Nice-to-Have:

• Exposure to ML pipelines, feature stores, or AI platforms.
• Experience in financial services or regulated environments.
• Understanding of data governance and security best practices