Data Engineer

Job not on LinkedIn

🕒 March 19

🇺🇸 United States – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 53%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Saaf Finance

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

💳 Fintech

🤖 Artificial Intelligence

☁️ SaaS

Fintech • Artificial Intelligence • SaaS

Saaf Finance is an AI-driven underwriting platform for mortgage lenders. Saaf’s AI Underwriter automates mortgage underwriting across products such as Non-QM, RTL, HELOC, DSCR, Jumbo, and Bank Statement loans, using OCR, large language models, and API integrations with data vendors and loan origination systems (e. g. , Encompass, MeridianLink). The platform produces structured “Source of Truth” loan data, reduces fraud risk through direct data connections, and claims substantial operational gains (faster processing, lower cost, and greater scalability). Saaf positions itself as a B2B partner to mortgage operations and secondary market participants, leveraging a training set of 200K+ loans and decades of industry experience to augment underwriters rather than replace them.

📋 Description

• Design, implement, and maintain ETL/ELT pipelines for structured and unstructured datasets from internal and external sources. • Build and optimize warehouses and marts (e.g., Snowflake, BigQuery) for analytics, reporting, and product use cases. • Ingest data from APIs and SaaS platforms (e.g., CRM, financial data APIs) into the core data platform. • Design conceptual, logical, and physical models to deliver scalable, consistent, high‑quality datasets. • Implement validation, schema management, and documentation to ensure accuracy and compliance. • Monitor and tune pipeline/warehouse performance for scalability and cost efficiency. • Apply data security and privacy controls aligned with financial regulations; ensure full transformation traceability. • Deliver clean, consistent datasets to analysts, PMs, and operations for fast, data‑driven decisions.

🎯 Requirements

• Bachelor’s/Master’s in CS, Engineering, or related field. • 3+ years in data engineering or similar backend data‑focused role. • Strong SQL and Python for transformation and automation. • Experience with modern ETL/ELT frameworks (e.g., dbt). • Proficiency with cloud platforms (AWS preferred) and serverless data services. • Strong experience with data warehouses (Snowflake preferred). • Skilled in API integrations and ingestion from third‑party systems. • Proficient in data modeling (Kimball/Star, Data Vault). • Able to implement CI/CD for data workflows and set up logging/monitoring/alerting for jobs.

🏖️ Benefits

• Competitive salary; high ownership from day one. • Fast decision cycles; remote‑first with flexibility on hours/location. • Direct access to founders; clear expectations, regular feedback, and growth support. • Work on complex, high‑impact problems in a data‑intensive industry.

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