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
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
Work Arrangement
Remote (City/Region) — New York
Additional Information
- Fair employment and equal opportunities: Data Intellect is an equal opportunity employer.
- Accommodations are available on request throughout the assessment and selection process.
