Financial Data Engineer - Python with Linux. Must be based in NY with right to work.

Data Intellect•New York, NY

6d•Onsite

About The Position

At Data Intellect, we focus on using data and technology as tools to provide solutions for complex challenges through human intellect and collaboration. We are problem solvers who are humble, possess a can-do attitude, and prioritize togetherness. We are looking for individuals who are not big on egos but are also not faint-hearted. This role involves implementing, configuring, and evolving SaaS data products within client environments. You will own the technical delivery of these implementations, ensuring robust integration into client data platforms, workflows, and operating models. You will work on long-running client engagements, developing a deep understanding of client needs and acting as a trusted technical partner. The position requires designing and implementing integration patterns, data pipelines, and solution architectures for scalability. You will deliver high-quality, production-ready solutions, balancing product constraints with client-specific requirements and best practices. Collaboration with product, engineering, and client stakeholders is key to influencing roadmaps and enhancements. You will also provide technical leadership and mentoring to junior team members, contribute to our learning and development ecosystem, and identify improvements to product usage and architecture. The role emphasizes producing clean, maintainable, and well-documented solutions, and continuing personal capability building through hands-on delivery and exposure to diverse clients and industries.

Requirements

MUST BE CURRENTLY BASED IN NEW YORK
MUST HAVE THE RIGHT TO WORK IN THE USA
MUST HAVE EXPERIENCE IN THE INVESTMENT BANKING DOMAIN
MUST HAVE MINIMUM 3 YEARS' COMMERCIAL EXPERIENCE IN PYTHON ENGINEERING
MUST HAVE LINUX EXPERIENCE
MUST HAVE EXPERIENCE WITH KUBERNETES, APACHE AIRFLOW, PANDAS AND POLARS
Minimum 3+ years Python experience in Data Science and Engineering
Experience with Kubernetes, Apache Airflow, Pandas, Polars
In-depth of knowledge across data science and engineering and software delivery
Development and delivery experience of data-driven applications and solutions
Capable of task estimation, proactive and autonomous
Solid knowledge of SDLC, agile and appropriate tooling
Breadth of L3 support experience
Excellent communication skills across peers, leadership and clients; both business and technical

Responsibilities

Implement, configure and evolve SaaS data products within client environments, taking solutions from initial onboarding through to long‑term adoption and optimisation
Own the technical delivery of SaaS implementations, ensuring products are robustly integrated into client data platforms, workflows and operating models
Work on long‑running client engagements, developing a deep understanding of client needs and acting as a trusted technical partner over time
Design and implement integration patterns, data pipelines and solution architectures that enable SaaS products to scale effectively for each client
Deliver high‑quality, production‑ready solutions, balancing product constraints with client‑specific requirements and best practice engineering standards
Collaborate closely with product, engineering and client stakeholders to influence roadmaps, enhancements and implementation approaches
Provide technical leadership and mentoring to junior team members, including guidance on SaaS delivery patterns, integration approaches and good engineering practices
Contribute to and help shape our learning & development ecosystem, sharing implementation learnings, patterns and reusable assets across teams
Identify and recommend improvements to product usage, configuration or architecture based on real‑world client exposure
Produce clean, maintainable and well‑documented solutions aligned to product standards and client specifications
Continue to build your own capability through hands‑on delivery, certification and exposure to multiple clients and industries