Data Intellect
Financial Markets
DataEngineer-Python
Neural analysis suggests this role is
optimal for mid candidates.
“Data Engineer - Python at Data Intellect. Skills: Data Engineering, Python, SaaS Implementation. Implement SaaS data products. Configure SaaS data products”
Industry & Context.
Problem solvers
What They're Looking For.
Must Have
3+ years Python experience, Minimum 3+ years Python experience in Data Science and Engineering, Experience with Kubernetes, Experience with Apache Airflow, Experience with Pandas, Experience with Polars, In-depth 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, Solid knowledge of agile, Solid knowledge of appropriate tooling, Breadth of L3 support experience, Excellent communication skills across peers, Excellent communication skills across leadership, Excellent communication skills across business, Excellent communication skills across technical
Nice to Have
Kubernetes experience a plus
What You'll Do.
Implement SaaS data products
Configure SaaS data products
Evolve SaaS data products
Own technical delivery of SaaS implementations
Integrate products into client data platforms
Integrate products into client workflows
Integrate products into client operating models
Develop deep understanding of client needs
Act as trusted technical partner
Design integration patterns
Implement integration patterns
Design data pipelines
Implement data pipelines
Design solution architectures
Implement solution architectures
Deliver production-ready solutions
Collaborate with product stakeholders
Collaborate with engineering stakeholders
Collaborate with client stakeholders
Influence enhancements
Influence implementation approaches
Provide technical leadership
Mentor junior team members
Guide on SaaS delivery patterns
Guide on integration approaches
Guide on engineering practices
Contribute to learning & development ecosystem
Share implementation learnings
Share reusable assets
Identify improvements to product usage
Recommend improvements to product configuration
Recommend improvements to product architecture
Produce clean solutions
Produce maintainable solutions
Produce well-documented solutions
How You'll Work.
Team & Collaboration
Client environments; Product teams; Engineering teams; Client stakeholders
Communication Scope
Technical partner; Client needs; Stakeholders
Process & Methodology
Agile, Task estimation
Full Job Description
At Data Intellect it has never been just about data or technology, they are our tools. It’s about human intellect, collaboration and providing solutions for the most complex of challenges. We do this by living the [DI] code: We are Problem Solvers who are Humble , possess a Can-do Attitude with a focus on Togetherness. “We are not big on egos, but we’re not for the faint-hearted either” – Steve Turner, CEO 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
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