Job Description

What you’ll be doing:

• 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

Qualifications

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 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

Additional Information

A little background on DI

Simply put – we turn big data problems into smart 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.

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