Sr. Data Engineer
About The Position
Sciemo builds AI for consumer goods: technology that helps businesses make faster, smarter, and more human decisions across the entire Sales and Operations Planning (S&OP) cycle. From optimizing promotions to balancing demand and supply, Sciemo's platform transforms messy, siloed data into measurable business impact. Its AI agents assist decision-makers in real-time, turning complexity into clarity. We are headquartered in New York City. We are an industry-leading startup developing AI for consumer brands. Our solutions leverage machine learning, generative AI, agent-based systems, and graph technologies to get our customers to insights in seconds and to business impact in minutes using our products. We are looking for our Founding Senior Data Engineer responsible for designing and maintaining the cloud‑native data platform that powers our analytics and ML products.
Requirements
- Proven track record of deploying AI products into customer environment
- Strong grasp of core machine learning, genai, agent and graph concepts, and best practices.
- Experience building a customer success team
- Demonstrated self-motivation, hacking mentality, and creative problem-solving abilities.
- Experience contributing thought leadership and driving innovation for AI within a customer context.
Responsibilities
- Cloud Data Pipeline Design & Development: Build scalable, cost‑effective ETL/ELT pipelines with AWS Glue, Athena, Redshift, S3, and Lambda (Python). Integrate data from diverse source systems (REST, streaming, databases, SaaS) and standardize into business‑specific target models (dimensional, lakehouse, or graph schemas). Leverage orchestration frameworks (Apache Airflow, AWS Step Functions) and versioned SQL/Python transformations (dbt or similar) to enable repeatable deployments.
- Data Governance, Lineage & Privacy: Implement data lineage and catalog solutions (DataHub, Amundsen, or OpenMetadata) ensuring end‑to-end traceability. Enforce data governance and control‑plane policies using AWS Lake Formation or equivalent, aligning with SOC 2, ISO 27001, GDPR, and CCPA requirements. Champion data‑quality SLAs, automated testing, and monitoring (Great Expectations, Monte Carlo, or similar).
- Collaboration & Enablement: Partner with ML Engineers and Data Scientists to provision feature stores and training datasets. Work with Backend Engineers to design efficient APIs and streaming interfaces for real‑time data access. Document data models, publish best practices, and mentor junior engineers on modern data‑engineering standards.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
