Data Engineer II

Key Responsibilities:

• Build and optimize experimental data pipelines to ingest, clean, and transform structured and unstructured data.
• Implement workflow orchestration using tools like Apache Airflow or Luigi for reproducibility and scalability.
• Collaborate with Data Scientists to design and implement feature extraction and transformation strategies.
• Develop reusable feature stores and maintain metadata for experimental datasets.
• Partner closely with Data Science teams to understand modeling requirements and ensure alignment between experimental and production environments.
• Provide technical guidance on data quality, schema design, and performance optimization.
• Evaluate emerging technologies and frameworks to enhance data engineering capabilities.
• Drive adoption of best practices in data governance, version control, and CI/CD for data workflows.

Qualifications

• Bachelor’s degree in computer science, engineering, or related field. Or comparable work experience.
• 4-8 years of experience in data engineering for data science and analytics.
• Hands-on experience with Python, SQL, and distributed systems.
• Familiarity with cloud platforms (GCP preferred).
• Strong understanding of data modeling, ETL processes, and feature engineering techniques.
• Experience with data pipeline orchestration tools and version control systems.
• Ability to work in Agile, cross-functional teams.