Data Engineer,Senior
About the Company
Quantiphi is an AI-first digital engineering and consulting company that helps organizations solve complex business challenges through intelligent, scalable AI solutions. Founded in 2013 and headquartered in Boston, the company has more than 4,000 professionals serving clients across industries, including banking, financial services and insurance (BFSI), healthcare and life sciences, consumer packaged goods, manufacturing, and technology, media, and entertainment. Quantiphi combines industry expertise, cloud and data engineering, and applied AI research to deliver measurable business outcomes. The company partners with leading technology platforms, including NVIDIA, Google Cloud, AWS, and Snowflake, and has received multiple industry awards and analyst recognitions.
About the Role
Quantiphi is seeking a Senior Data Engineer with 8+ years of experience to design, build, and optimize high-performance data infrastructure supporting Asset-Backed Finance (ABF) investment and portfolio analytics. This full-time, remote position in the United States will focus on modern data platform development, scalable ETL/ELT architecture, and cloud-based data engineering. The successful candidate will lead data platform initiatives using Snowflake, orchestrate complex workflows with Dagster, and leverage AWS services to develop reliable data pipelines. The role also involves supporting legacy system migrations, maintaining financial data integrity, and contributing to project planning and cross-functional coordination to ensure successful delivery.
Key Responsibilities
Design, build, and maintain cloud-native data pipelines and data lake architectures using Snowflake to support ABF investment and portfolio analytics. Develop and manage scalable ETL/ELT workflows to ingest, transform, and curate structured and unstructured data. Support analytics and reporting requirements, including data reconciliation, validation, and financial data integrity checks. Support migration from legacy systems to a modern data platform, including data mapping, transformation logic, and architecture alignment. Design and maintain enterprise data models and warehouse architectures for financial services, investment management, and portfolio analytics use cases. Optimize Snowflake data warehouse performance, architecture, security, and schema design. Use Dagster for workflow orchestration, dependency management, and pipeline monitoring. Leverage AWS services to support cloud infrastructure and data engineering requirements. Break down project work into epics and user stories in Jira. Support project planning, timeline management, and coordination across teams. Assist with testing, cutover planning, and go-live readiness. Collaborate with cross-functional teams to support successful implementation and delivery of data platform initiatives. Required Qualifications 8+ years of progressive experience in data engineering, data platform development, or enterprise analytics. Proven experience building enterprise data models and data warehouse architectures in financial services, investment management, or Asset-Backed Finance and portfolio analytics environments. Advanced proficiency in Snowflake, including SQL performance tuning, architecture, security, and schema design. Hands-on experience with Dagster for workflow orchestration, dependency management, and monitoring. Strong knowledge of AWS services, such as S3, Glue, Lambda, IAM, ECS, EMR, or Redshift. Expert-level proficiency in Python and advanced SQL for complex data transformations and ELT design. Proficiency in Jira for backlog management and Agile sprint planning. Employment Type and Work Arrangement Position: Senior Data Engineer Employment Type: Full-time Experience Level: 8+ years Work Location: Remote, United States Why Join Quantiphi Be part of an AI-first digital transformation and engineering company working on complex data, cloud, and AI challenges. Collaborate with a team of talented professionals across data engineering and technology. Gain exposure to Fortune 500 companies and innovative market disruptors. Work with modern technologies in artificial intelligence, machine learning, data engineering, and cloud computing.