Senior Data Engineer (Power BI)

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. 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.21x Google Cloud Partner of the Year awards in the last 8 years.~3x AWS AI/ML award wins.~Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovation.

We are seeking an experienced Senior Data Engineer with 8+ years of expertise to design, build, and optimize high-performance data infrastructure supporting Asset-Backed Finance (ABF) investment and portfolio analytics. In this role, you will lead the modern data platform initiatives, building robust ETL/ELT architecture in Snowflake, orchestrating complex workflows with Dagster, and leveraging modern AWS cloud services. You will also support critical migration efforts from legacy systems and contribute light project management oversight to ensure smooth, cross-functional execution. Design, build, and maintain cloud-native data pipelines and datalake architectures (Snowflake) to support ABF investment and portfolio analytics Develop and manage scalable ETL/ELT workflows to ingest, transform, and curate data from structured and unstructured sources Support analytics and reporting use cases, including data reconciliation, validation, and financial data integrity checks Support the migration from legacy systems to a modern data platform, including data mapping, transformation logic, and architecture alignment Contribute to light project management activities, including: Breaking down work into Epics/User Stories (Jira) Supporting project planning, timelines, and coordination across teams Assisting with testing, cutover planning, and go-live readiness 8+ years of progressive experience in data engineering, data platform development, or enterprise analytics.~ Proven track record building enterprise data models and warehouse architectures within financial services, investment management, or ABF/portfolio analytics domain contexts.~ Data Warehousing: Advanced proficiency in Snowflake (SQL performance tuning, architecture, security, and schema design).~ Hands-on expertise using Dagster for workflow orchestration, dependency management, and monitoring.~ Cloud Infrastructure: Deep familiarity with core AWS services (e.g., Data Pipelines & Languages: Expert-level mastery of Python and advanced SQL for complex data transformation and ELT design.~ Tooling & PM: Proficient with Jira for backlog management and Agile sprint planning. Be part of the fastest-growing AI-first digital transformation and engineering company in the world 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