Solution Engineer

Overview

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence.

Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Please visit Fractal | Intelligence for Imagination for more information about Fractal

Location:

NYC, New York (Onsite)

Note:

This position is not eligible for Immigration Sponsorship at this time.

We are seeking an experienced Solution Engineer to bridge the gap between business intake and technical delivery for data and analytics use cases. This role is responsible for translating product and business requirements into pragmatic, end-to-end technical solutions that can be confidently handed off to delivery teams.

Solution Engineers operate at the intersection of architecture, platform engineering, and delivery planning. They ensure that use cases are technically feasible, aligned to platform standards, and positioned for rapid execution—without requiring exhaustive upfront design.

This role will support multiple domains and a growing portfolio of use cases built on Databricks and/or Google Cloud.

Intake & Requirements Translation

• Review PRDs and intake artifacts to assess:
• Functional requirements
• Data sources and dependencies
• Success criteria and value drivers
• Identify gaps, ambiguities, and assumptions requiring clarification
• Ensure PRDs remain focused on what is needed, not how it is built
• Define end-to-end technical solutions, including:
• Data ingestion and transformation approaches
• Platform services and components (Databricks, GCP)
• Analytics, modeling, and consumption patterns
• “Just enough” architecture to start delivery
• Decide when use cases require:
• Proofs of concept (POCs)
• Direct progression to build and production

Platform & Feasibility Assessment

• Evaluate use cases against:
• Platform readiness
• Data availability and quality
• Security, governance, and operational constraints
• Delivery sequencing
• Effort and complexity estimation
• Technical risk identification

Delivery Enablement

• Serve as the technical handoff point to development teams
• Collaborate with delivery leads to:
• Clarify architectural intent
• Adjust designs as implementation realities emerge
• Support agile delivery by updating solution artifacts as needed
• Work closely with:
• Intake and product teams
• Platform and data engineering teams
• Analytics and data science teams
• Help establish and evolve:
• Feedback loops between intake and delivery

Technical & Platform Expertise

• Databricks (data engineering, analytics, lakehouse patterns)
• Google Cloud Platform, including relevant data and analytics services
• Solid understanding of:
• Data pipelines and transformations
• Analytical and reporting use cases

Solution Engineering & Architecture

• Proven experience translating business requirements into technical designs
• Comfort operating with incomplete or evolving requirements
• Ability to balance speed, rigor, and pragmatism

Delivery & Agile Mindset

• Experience working with agile delivery teams
• Understanding of how design evolves during implementation
• Focus on enabling progress rather than perfect upfront specification

Communication & Influence

• Ability to clearly articulate technical decisions to both technical and non-technical stakeholders
• Comfortable acting as a point of alignment across multiple teams and domains

Nice to Have

• Experience in regulated or enterprise environments
• Familiarity with analytics or advanced analytics use cases
• Exposure to multi-domain or portfolio-scale delivery models

Pay

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and…