Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Associate Technical Architect - Data - USA
USA - Remote
Actively hiring, first seen by us today- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
Remote — work setting source
Listed location: USA - Remote
Read the full posting- Employment
Full-time — employment source
Experience Level: 8+ years Employment Type: Full time Role Summary:
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingWe are seeking an experienced Senior ATA – Data to bridge the gap between enterprise data architecture, execution, and product delivery.
The ideal candidate brings deep domain expertise in financial services—specifically alternative investments—paired with senior-level hands-on data engineering chops (Snowflake, Python, advanced SQL) and proven delivery acumen across the full software and data development lifecycle.
Build and maintain cloud data pipelines and datalakes on Snowflake
Design automated ETL/ELT ingestion and transformations for financial datasets
Lead migrations from legacy data stores to modern architectures
Implement reconciliation, schema validation and data integrity checks
Drive product roadmaps and prioritize technical backlogs in Jira
From the employer’s posting
We are seeking an experienced Senior ATA – Data to bridge the gap between enterprise data architecture, execution, and product delivery. In this dual-impact technical leadership role, you will architect scalable cloud data pipelines and datalakes while driving core technical product and program management workflows.
The ideal candidate brings deep domain expertise in financial services—specifically alternative investments—paired with senior-level hands-on data engineering chops (Snowflake, Python, advanced SQL) and proven delivery acumen across the full software and data development lifecycle.
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
Implement end-to-end data reconciliation, schema validation, de-duplication, and financial data integrity checks
Drive product roadmaps, groom and prioritize technical backlogs
What you’ll bring
All qualificationsCore experience
- 8+ years of hands-on data engineering, technical product management, or technical architecture experience.
- 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.
- 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.
Qualification wording
8+ years of hands-on data engineering, technical product management, or technical architecture experience.
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.
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.
Education & alternatives
- 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. What is in it for you:
About Quantiphi
As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 4, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
Quantiphi is hiring
30 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is steady
- Takes jobs down at a usual pace
- 3% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- dbt
- GCP
- Prefect
- Snowflake
- Airflow
- Dagster
- pandas
- Polars
- PySpark
Where the posting names them
We are seeking an experienced Senior ATA – Data to bridge the gap between enterprise data architecture, execution, and product delivery. In this dual-impact technical leadership role, you will architect scalable cloud data pipelines and datalakes while driving core technical product and program management workflows. The ideal candidate brings deep domain expertise in financial services—specifically alternative investments—paired with senior-level hands-on data engineering chops (Snowflake, Python, advanced SQL) and proven delivery acumen across the full software and data development lifecycle. Responsibilities:
- 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.
- 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).
Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact. Our industry recognition includes:
- 21x Google Cloud Partner of the Year awards in the last 8 years. - 3x AWS AI/ML award wins. - 3x NVIDIA Partner of the Year titles.
- 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.
Our industry recognition includes: - 21x Google Cloud Partner of the Year awards in the last 8 years. - 3x AWS AI/ML award wins.
- 3x NVIDIA Partner of the Year titles. - 2x Snowflake Partner of the Year awards. - Top analyst recognitions from Gartner, ISG, and Everest Group.
Responsibilities: - Cloud-Native Data Platforms: Architect, construct, and maintain resilient cloud data pipelines and modern datalake environments powered by Snowflake. - ETL/ELT Pipeline Development: Design and manage automated, high-throughput ingestions and transformations across structured, semi-structured, and unstructured financial datasets.
Your next step
Complete your application on quantiphi.wd1.myworkdayjobs.com. The employer’s form will show what is required.
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Already applied? Track this application
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
About Quantiphi:
Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations.
Since our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake.
Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc.
As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.
Our industry recognition includes:
- 21x Google Cloud Partner of the Year awards in the last 8 years.
- 3x AWS AI/ML award wins.
- 3x NVIDIA Partner of the Year titles.
- 2x Snowflake Partner of the Year awards.
- Top analyst recognitions from Gartner, ISG, and Everest Group.
- Consecutive certifications as a Great Place to Work.
Be part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.
Your next big opportunity starts here!
Work Location: New York, USA
Experience Level: 8+ years
Employment Type: Full time
Role Summary:
We are seeking an experienced Senior ATA – Data to bridge the gap between enterprise data architecture, execution, and product delivery. In this dual-impact technical leadership role, you will architect scalable cloud data pipelines and datalakes while driving core technical product and program management workflows.
The ideal candidate brings deep domain expertise in financial services—specifically alternative investments—paired with senior-level hands-on data engineering chops (Snowflake, Python, advanced SQL) and proven delivery acumen across the full software and data development lifecycle.
Responsibilities:
- Cloud-Native Data Platforms: Architect, construct, and maintain resilient cloud data pipelines and modern datalake environments powered by Snowflake.
- ETL/ELT Pipeline Development: Design and manage automated, high-throughput ingestions and transformations across structured, semi-structured, and unstructured financial datasets.
- Legacy Modernization & Migration: Lead migration initiatives from legacy data stores to modern data architectures, establishing robust data mapping frameworks, transformation logic, and architectural consistency.
- Data Quality & Integrity: Implement end-to-end data reconciliation, schema validation, de-duplication, and financial data integrity checks supporting mission-critical analytics and regulatory reporting.
- Roadmapping & Prioritization: Drive product roadmaps, groom and prioritize technical backlogs, and balance feature delivery against technical debt and platform reliability.
- Full-Lifecycle Execution: Spearhead initiatives across all phases—from business requirements gathering and technical design through development, integration testing, user acceptance testing (UAT), cutover planning, and go-live execution.
- Agile Orchestration: Break down high-level strategic objectives into epics, technical user stories, and acceptance criteria in Jira.
- Stakeholder Management & Change Enablement: 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.
Required Skills:
- 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.
What is in it for you:
- 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
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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