Q

Quantiphi

AI-driven digital transformation and automation services

Associate Technical Architect - Data

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

  • At least 8 years of hands-on data engineering, technical product management, or technical architecture experience.
  • Strong financial-services domain knowledge, including direct experience handling sensitive financial data in alternative investments such as private equity, hedge funds, private credit, or real estate.
  • At least 8 years of production-grade Python development for large-scale data processing, performance optimization, and automation using Pandas, Polars, PySpark, or equivalent.
  • At least 8 years writing advanced SQL, including complex window functions, common table expressions, recursive queries, dynamic conditional logic, and database query optimization.
  • Production experience deploying and optimizing solutions on Snowflake and associated cloud ecosystems such as AWS, Azure, or GCP.
  • Experience 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 such as Airflow, Prefect, or Dagster and data transformation frameworks such as dbt.
  • Experience navigating regulatory and governance standards such as SOC 2, GDPR, and BCBS 239 within buy-side or sell-side financial institutions.
  • A Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Finance, or a related quantitative discipline.

Responsibilities

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

About the Company

Quantiphi

AI-driven digital transformation and automation services

Quantiphi uses AI and digital engineering to help organizations transform by making products and operations smarter and safer. It partners with clients to understand their challenges and then designs and builds customized AI and automation systems—combining machine learning, data analytics, and software engineering—delivering them under long-term contracts with ongoing support, and collaborating with Google Cloud to integrate technologies. Compared with competitors, it provides end-to-end, tailored solutions across industries rather than one-off projects, backed by long-term relationships and strong technology partnerships to scale. Its goal is to embed AI into products and processes to improve customer experiences and overall efficiency.

Company size
1,001-5,000
Company stage
Series A
Total funding
$23.4M
Headquarters
Marlborough, MA
Founded
2013

Recently Posted Jobs

Explore more opportunities at Quantiphi

See more jobs