Senior Data Engineer

Quantiphi

. Design, build, and maintain cloud-native data pipelines and data lake architectures in Snowflake for Asset-Based Finance investment and portfolio analytics .

Posted 10/16/2026full-timeRemote • New York • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in designing and maintaining cloud-native data pipelines and data lake architectures, with a strong focus on ETL/ELT workflows and quantitative finance applications. Proven ability to manage full lifecycle projects, ensuring data integrity and effective communication across teams.

Highest-signal resume keywords

Data EngineeringETL/ELT WorkflowsAdvanced SQLPython DevelopmentProduct/Program Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline OptimizationData MappingData Transformation LogicData CleaningData ReconciliationCashflow ModelsPredictive ModelsBacktestingComplex Window FunctionsConditional Logic

Soft Skills

Good Communication SkillsChange Management Abilities

Tools & Technologies

SnowflakeJiraPolarsPandas

Industry Keywords

Mortgage Whole LoanRMBSStructured CreditCredit RiskFixed Income Fundamentals

Tech Stack

Tools & technologies

CloudETLPandasPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain cloud-native data pipelines and data lake architectures in Snowflake for Asset-Based Finance investment and portfolio analytics
Develop and manage scalable ETL/ELT workflows to ingest, transform, and curate structured and unstructured data
Support analytics and reporting use cases, including data reconciliation, validation, and financial data integrity checks
Support migration from legacy systems to a modern data platform through data mapping, transformation logic, and architecture alignment
Break down work into Epics and User Stories in Jira
Support project planning, timelines, and coordination across teams
Assist with testing, cutover planning, and go-live readiness
Bridge engineering, quantitative analytics, and project execution while translating quantitative financial logic into scalable ETL/ELT architecture

Requirements

What you’ll need

8+ years of experience
Demonstrated experience in data engineering, including building, maintaining, and optimizing data pipelines and workflows
Mortgage Whole Loan and RMBS industry experience preferred
Quantitative finance knowledge, including cashflow models, predictive models, backtesting, and calibration
Structured credit knowledge preferred; credit risk and fixed income fundamentals helpful
Good communication skills and change management abilities
Product/Program Management experience leading a full lifecycle project, including requirements, design, build, testing, cutover planning, and go-live execution
5+ years of advanced SQL experience, including CTEs, complex window functions, conditional logic, joins, and aggregations
Experience with data cleaning, de-duplication, and reconciliation
5+ years of professional Python development for processing complex datasets and automation using Polars, Pandas, or equivalent

Benefits

Comp & perks

Exposure to working with Fortune 500 companies and innovative market disruptors
Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud
Opportunity to be part of an energetic team of highly dynamic and talented individuals
Opportunity to work at a fast-growing AI-first digital transformation and engineering company