Note: The job is a remote job and is open to candidates in USA. Tixy Tech is seeking an experienced Senior Quant Data Engineer to design, build, and optimize high-performance data platforms for structured finance and asset-backed securities. The role involves collaborating with quantitative analysts and data engineers to ensure data accuracy and scalability while developing scalable, AI-native data solutions.
Responsibilities
- Design, develop, and optimize high-performance Python-based data pipelines using Polars, Pandas, and Apache Spark
- Build scalable ingestion and normalization pipelines for daily and monthly servicer feeds covering:
- Mortgage portfolios
- Whole loans
- Asset-Backed Securities (ABS)
- HELOCs
- Student loans
- RV and specialty lending portfolios
- Architect resilient ETL workflows including error handling, reconciliation, monitoring, and recovery mechanisms
- Develop production-grade reconciliation frameworks to validate current vs. target LMS data models
- Own quantitative tie-out processes ensuring data integrity across large-scale financial datasets (100K+ loan records)
- Design and optimize Snowflake data models supporting portfolio analytics, reporting, and AI-driven insights
- Implement dimensional, star schema, snowflake schema, and Data Vault modeling patterns
- Build automated data quality validation, anomaly detection, and production monitoring frameworks
- Partner with migration teams to support enterprise LMS migration initiatives and production cutovers
- Develop Python-based analytics dashboards using Plotly Dash and Snowflake-backed datasets
- Optimize Snowflake warehouse performance, storage utilization, and SQL execution efficiency
- Maintain metadata, lineage, governance, and access controls across enterprise data platforms
- Collaborate closely with quantitative analysts, software engineers, business users, and executive stakeholders throughout the SDLC
- Support CI/CD deployment pipelines for enterprise data engineering solutions
Skills
- Bachelor's or master's degree in computer science, Data Engineering, Quantitative Finance, Financial Engineering, Applied Mathematics, Statistics, or a related discipline
- 7–10 years of experience designing and maintaining enterprise data engineering platforms
- Strong experience within Financial Services, Asset Management, Structured Finance, or Capital Markets
- Hands-on experience supporting: Asset-Backed Securities (ABS), Mortgage portfolios, Whole loans, HELOCs, Student loans, Structured credit products
- Expert-level Python programming experience
- Strong expertise with: Polars, Pandas, Apache Spark
- Advanced experience designing Snowflake data warehouses
- Strong SQL development and query optimization skills
- Experience building large-scale reconciliation frameworks
- Experience normalizing multi-servicer financial datasets
- Expertise implementing automated data quality validation and anomaly detection
- Experience with Azure Data Factory or comparable enterprise ETL orchestration tools
- Experience implementing CI/CD for enterprise data pipelines
- Excellent analytical, quantitative, and problem-solving skills
- Strong communication skills with the ability to explain complex quantitative concepts to technical and business audiences
- Experience building AI-native data engineering workflows using Cursor AI, MCP, or similar AI-assisted development tools
- Experience developing Python analytics dashboards using Plotly Dash
- Familiarity with Tableau reporting environments
- Experience with streaming or near real-time financial data ingestion
- Knowledge of quantitative financial modeling including: Cashflow modeling, Prepayment models, Default modeling, Loss severity modeling
- Experience supporting LMS platforms such as Black Knight MSP or similar servicing platforms
- Experience within institutional asset managers, private credit firms, or investment organizations
- Exposure to organizations similar to Blackstone, Apollo, SoFi, or comparable financial institutions
- Snowflake SnowPro Core or Advanced Data Engineer certification
- AWS Certified Data Analytics – Specialty certification
- Azure Data Engineer Associate certification
- CFA or FRM certification
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