Associate Technical Architect – Data

Quantiphi

. Architect, construct, and maintain resilient cloud data pipelines and modern datalake environments powered by Snowflake .

Posted 11/3/2026full-timeRemote • New York • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and maintaining cloud data pipelines and modern datalake environments, particularly with Snowflake. Proficient in managing complex financial datasets and ensuring data integrity while navigating regulatory standards.

Highest-signal resume keywords

Cloud Data Pipeline ArchitecturePython Development for Data ProcessingAdvanced SQL ExpertiseSnowflake Deployment and OptimizationFinancial Services Domain Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData TransformationData ReconciliationPerformance OptimizationAutomated IngestionSchema ValidationComplex SQL QueriesData Mapping FrameworksProject Lifecycle ManagementRegulatory Compliance

Soft Skills

LeadershipCollaborationRisk ManagementCommunicationProblem-Solving

Tools & Technologies

SnowflakeJiraConfluenceAirflowPandasPolarsPySparkAWSAzureGCP

Industry Keywords

Financial ServicesAlternative InvestmentsPrivate EquityHedge FundsPrivate CreditReal EstateSOC2GDPRBCBS 239

Tech Stack

Tools & technologies

AirflowAWSAzureCloudGoogle Cloud PlatformPandasPySparkPythonSnowflakeSQL

About the role

Key responsibilities & impact

Architect, construct, and maintain resilient cloud data pipelines and modern datalake environments powered by Snowflake
Design and manage automated, high-throughput ingestions and transformations across structured, semi-structured, and unstructured financial datasets
Lead migration initiatives from legacy data stores to modern data architectures, establishing robust data mapping frameworks, transformation logic, and architectural consistency
Implement end-to-end data reconciliation, schema validation, de-duplication, and financial data integrity checks supporting mission-critical analytics and regulatory reporting
Drive product roadmaps, groom and prioritize technical backlogs, and balance feature delivery against technical debt and platform reliability
Lead initiatives across all phases, from business requirements gathering and technical design through development, integration testing, user acceptance testing, cutover planning, and go-live execution
Break down high-level strategic objectives into epics, technical user stories, and acceptance criteria in Jira
Serve as the central conduit between business users, quant/analytics teams, and engineering leads; proactively escalate risks, align timelines, and ensure operational readiness during platform rollouts

Requirements

What you’ll need

8+ years of hands-on data engineering, technical product management, or technical architecture experience
Strong domain knowledge of financial services, with direct experience handling sensitive financial data within the alternative investments space (e.g., Private Equity, Hedge Funds, Private Credit, Real Estate)
8+ years of production-grade Python development focusing on large-scale data processing, performance optimization, and automation using libraries such as Pandas, Polars, PySpark, or equivalent
8+ years writing advanced SQL, including deep expertise in complex Window Functions, Common Table Expressions (CTEs), recursive queries, dynamic conditional logic, and database query optimization
Demonstrated production experience deploying and optimizing solutions on Snowflake and associated cloud ecosystems (AWS, Azure, or GCP)
Proven background managing end-to-end project lifecycles, release management, operational cutover plans, and Jira/Confluence delivery frameworks
Experience designing automated continuous reconciliation frameworks for complex accounting, portfolio, or transactional data
Familiarity with modern orchestration tools (e.g., Airflow, Prefect, Dagster) and data transformation frameworks (e.g., dbt)
Experience navigating regulatory and governance standards (e.g., SOC2, GDPR, BCBS 239) within buy-side or sell-side financial institutions
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Finance, or a related quantitative discipline

Benefits

Comp & perks

Be part of the fastest-growing AI-first digital transformation and engineering company in the world
Be a part of an energetic team of highly dynamic and talented individuals
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