Senior Data Engineer

Job not on LinkedIn

🔥 4 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 19%

What it means: how likely this posting is sitting open without active hiring.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.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

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 • Leverage AI-assisted development tools to accelerate pipeline authoring, generate transformation logic, and automate boilerplate code • Build and optimize data warehouses and marts for analytics, reporting, and product use cases • Design, implement, and maintain conceptual, logical, and physical data models • Ingest data from APIs, SaaS platforms, and internal systems into the core data platform • Build and maintain reliable connectors and ingestion frameworks handling schema evolution, rate limits, and error recovery • Implement validation, schema management, and documentation for data accuracy and compliance • Use AI tools for data profiling, anomaly detection, and automated documentation of lineage and transformations • Evaluate and integrate emerging AI tools into the team's data development process • Build and support agentic workflows and multi-step automated processes acting on real-time data • Apply AI-assisted analysis to debugging pipeline failures, optimizing query performance, and identifying data quality issues • Monitor and fine-tune pipeline and warehouse performance for scalability and cost efficiency • Set up logging, monitoring, and alerting for data jobs • Apply data security and privacy controls aligned with financial regulatory requirements • Provide clean, consistent datasets for analysts, product managers, and operational teams • Collaborate with product managers, data scientists, and full stack engineers to align data models with business needs

🎯 Requirements

• 5+ years in a data engineering or similar backend data-focused role • Strong SQL and Python development skills for data transformation and automation • Experience with modern ETL/ELT frameworks such as dbt • Proficiency with cloud platforms (AWS preferred) and serverless data services • Strong experience with data warehouse technologies (Snowflake preferred) • Skilled in API integrations and ingestion from third-party systems • Proficient in data modeling (Kimball/Star schema, Data Vault) • Demonstrated, regular use of AI-powered development tools (e.g., Cursor, GitHub Copilot, Claude Code, or similar) to accelerate data pipeline development, debugging, or documentation • Proven track record of delivering production-grade data pipelines at scale • Experience implementing CI/CD practices for data workflows • Experience collaborating closely with product managers, data scientists, and full stack engineers • Startup mindset: hands-on, resourceful, and comfortable operating in a fast-paced environment • Preferred: Experience building agentic workflows and orchestrating multi-step automated processes that act on data in real time • Preferred: Familiarity with data engineering patterns and infrastructure required for AI-powered tools and automation platforms • Preferred: Experience working with financial datasets and APIs in a high-compliance environment • Preferred: Understanding of data privacy regulations such as GDPR and CCPA • Preferred: Experience with prompt engineering for code generation, data transformation logic, or building AI-powered data workflows

🏖️ Benefits

• Competitive salary • Unlimited PTO • Remote-first with flexible hours • Upto $2,000/year professional development budget • Home office setup stipend