Financial Data Engineer - Python with Linux. Must be based in NY with right to work.
đșđž United States
Python
Kubernetes
Finance
Design
SaaS
Data Science
Financial Data Engineer - Python with Linux. Must be based in NY with right to work.
from đșđž United States
At Data Intellect it has never been just about data or technology, they are our tools. Itâs about human intellect, collaboration and providing solutions for the most complex of challenges.
We do this by living the [DI] code:
We areProblem Solvers who areHumble, possess aCan-do Attitude with a focus onTogetherness.
âWe are not big on egos, but weâre not for the faint-hearted eitherâ â Steve Turner, CEO
What youâll be doing:
- Implement, configure and evolve SaaS data products within client environments, taking solutions from initial onboarding through to longâterm 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 longârunning 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 highâquality, productionâready solutions, balancing product constraints with clientâspecific 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 realâworld client exposure
- Produce clean, maintainable and wellâdocumented solutions aligned to product standards and client specifications
- Continue to build your own capability through handsâon delivery, certification and exposure to multiple clients and industries
Experience and skills required:
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 POLARSÂ
- Minimum 3+ years Python experience in Data Science and EngineeringÂ
- 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 autonomousÂ
- Solid knowledge of SDLC, agile and appropriate toolingÂ
- Breadth of L3 support experienceÂ
- Excellent communication skills across peers, leadership and clients; both business and technicalÂ
A little background on DI
Simply put â we turnbig data problems intosmart data solutions
At our core, Data Intellect is a data and technology consultancy firm. Our key area of expertise is financial and capital markets technology solutions. However, the utility of these solutions allow us to apply fintech data expertise to other industries such as smart energy and healthcare.
This proprietary offering is complemented by a wealth of experience in data engineering, electronic trading systems, data capture applications, regulatory and compliance systems and middle and back-office enterprise web solutions.
Fair employment and equal opportunities
Data Intellect is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Accommodations are available on request throughout the assessment and selection process.
Welcome to Data Intellect.
#ChallengeAccepted














