Senior Data Engineer
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Job Description
Senior Data Engineer designing and operating scalable data ingestion and web scraping systems for AI-driven valuation tools at art tech startup. Collaborating across teams to build intelligent features.
Responsibilities:
- Design and operate scalable data ingestion and web scraping systems
- Build batch and real-time pipelines to normalize, enrich, and version data across structured and unstructured sources
- Develop systems to support LLM- and ML-based document parsing, OCR, and classification
- Own the architecture of our data storage and processing stack, including PostgreSQL, data lakes, and data warehouses
- Operationalize AI/ML workflows by preparing clean training and inference datasets with robust lineage, validation, and error handling
- Integrate output with backend APIs, valuation services, and frontend analytics dashboards
- Collaborate across engineering and product to ship reliable, intelligent features quickly
- Contribute to our infrastructure tooling, including CI/CD, IaC (Terraform), and data observability
Requirements:
- Education: B.S. in Computer Science or equivalent
- Language: Fluency in English (written and spoken)
- Experience: 5+ years of experience building data platforms in production environments, ideally in startup or fast-moving contexts
- Technical Skills: Fluent in Python, SQL, and familiar with orchestration tools like Airflow, Dagster, or Temporal
- Have designed or maintained web scraping pipelines at scale, using best practices around retries, proxies, and anti-bot strategies
- Understand tradeoffs between ETL and ELT, and have hands-on experience with data lakes and data warehouses
- Have integrated structured and unstructured sources, and enjoy resolving messy edge cases that come with real-world data
- Have worked with LLM APIs or ML models in production, particularly for document understanding, NLP, or entity extraction
- Thrive in AI-native environments and enjoy building tools that support intelligent automation and analytics
- Care about clean architecture, versioning, reproducibility, and quality in data systems
Benefits:
- Equity option grants of company shares, offering alignment with company success
- Flexible remote work environment
- Paid time off, including vacation, sick leave, and local holiday
- Additional leave for bereavement or family emergencies
- Opportunities for continuous learning and skill development
- Access to training, courses, and knowledge-sharing sessions
- Mentorship and leadership development initiatives
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