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Saaf Finance
Saaf Finance
11 – 50 Darbinieki
FintechMākslīgais intelektsSaaS
Saaf Finance builds AI underwriting software for mortgage lenders. Its platform applies OCR, large language models, and connections to data providers and loan origination systems to organize loan information and support underwriting across products including Non-QM, RTL, HELOC, DSCR, jumbo, and bank statement loans. By drawing on a reported dataset of more than 200,000 loans, it aims to help mortgage operations and secondary market teams assess files, identify fraud risks, and process loans more efficiently. The company describes its software as augmenting underwriters’ work rather than replacing them.
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Vakances uzņēmumā

Senior Data Engineer – Saaf Finance (Remote, India)

Build scalable data pipelines, warehouses, and AI-enabled workflows for Saaf Finance’s mortgage lending platform. Support compliant underwriting, automation, and data-informed operations.

INIndijaAttālinātiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuDatu inženieris
AWSETLMākonisPythonSQLVault

Apraksts

  • Develop and maintain pipelines for structured and unstructured data from internal and external sources.
  • Use AI development tools to speed pipeline creation, generate transformation logic, and automate routine code.
  • Create and optimize warehouses and data marts for analytics, reporting, and product needs.
  • Design and maintain conceptual, logical, and physical data models.
  • Bring data from APIs, SaaS products, and internal systems into the core platform.
  • Maintain dependable connectors and ingestion frameworks that handle schema changes, rate limits, and failures.
  • Establish validation, schema controls, and documentation to support data quality and compliance.
  • Apply AI tools to data profiling, anomaly detection, and automated lineage and transformation documentation.
  • Assess and integrate new AI tools into the team’s data development practices.
  • Develop and support agentic workflows and multi-step automation using real-time data.
  • Use AI-assisted analysis to investigate pipeline failures, improve query performance, and find data quality issues.
  • Track and tune pipeline and warehouse performance for scale and cost efficiency.
  • Configure logging, monitoring, and alerts for data jobs.
  • Apply data security and privacy controls that meet financial regulatory requirements.
  • Deliver reliable, consistent datasets to analysts, product managers, and operations teams.
  • Work with product managers, data scientists, and full stack engineers to align data models with business needs.

Prasības

  • Bring at least five years of experience in data engineering or a similar backend data-focused role.
  • Have strong SQL and Python skills for data transformation and automation.
  • Have experience with modern ETL/ELT frameworks such as dbt.
  • Be proficient with cloud platforms, preferably AWS, and serverless data services.
  • Have substantial experience with data warehouses, preferably Snowflake.
  • Be skilled in API integrations and ingestion from third-party systems.
  • Be proficient in data modeling methods such as Kimball, star schema, and Data Vault.
  • Regularly use AI coding tools such as Cursor, GitHub Copilot, or Claude Code to accelerate pipeline development, debugging, or documentation.
  • Have delivered production-grade data pipelines at scale.
  • Have implemented CI/CD practices for data workflows.
  • Have collaborated closely with product managers, data scientists, and full stack engineers.
  • Be hands-on and resourceful, and comfortable in a fast-paced startup environment.
  • Preferred: Experience building agentic workflows and orchestrating multi-step automation on real-time data.
  • Preferred: Familiarity with data engineering patterns and infrastructure for AI-powered tools and automation platforms.
  • Preferred: Experience with financial datasets and APIs in a highly regulated environment.
  • Preferred: Understanding of data privacy regulations such as GDPR and CCPA.
  • Preferred: Experience with prompt engineering for code generation, data transformation, or AI-powered data workflows.

Priekšrocības

  • Competitive pay.
  • Unlimited paid time off.
  • Remote-first work with flexible hours.
  • Up to $2,000 per year for professional development.
  • Stipend for setting up a home office.

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