Senior Solutions Architect - Data & AI Platforms (Databrick) at TymeX

Johannesburg, Gauteng, South Africa -

Full Time

Start Date

Immediate

Expiry Date

22 Jan, 26

Salary

0.0

Posted On

24 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Solutions Architecture, Data Platforms, AI Platforms, Databricks, AWS, DevSecOps, DataOps, Machine Learning, Python, SQL, Infrastructure as Code, Orchestration, Stakeholder Engagement, Platform Reliability, Collaboration, Continuous Improvement

Industry

Software Development

Description

About Us At TymeX, we’re empowering Tyme Group’s digital banking ecosystem across Asia and Africa. Our mission: build a secure, scalable, intelligent data & AI platform that delivers real-time, personalized experiences to millions of users. We are seeking a Senior Solutions Architect – Data & AI Platforms — someone who blends deep technical mastery with the ability to engage directly with stakeholders, understand their business needs, and design/implement high-impact solutions. Your Role As a Senior Solutions Architect – Data & AI Platforms, you will be the trusted technical advisor to our stakeholders, guiding them through their data & AI journeys. You will represent TymeX’s capabilities across data, platform, DevSecOps, DataOps and ML infrastructure; you will both design and deliver production-grade systems built on Databricks + AWS, and you will engage with stakeholders to shape their roadmaps, architectures and success. You’ll partner with internal engineering teams, product teams and business stakeholders — translating business objectives into scalable technical solutions, delivering hands-on implementation when needed, and ensuring those solutions deliver tangible outcomes. What You’ll Do 1. Stakeholders Engagement & Solution Design Serve as a trusted advisor to stakeholders: understand their business goals, data challenges, ML/AI ambitions, and define technical strategies accordingly. Architect end-to-end data & ML solutions on Databricks + AWS: from ingestion, storage, processing, feature engineering, to model training, serving, monitoring and operations. Present and demonstrate solution architectures, proof-of-concepts, and reference implementations to technical & non-technical stakeholders. 2. Platform Architecture & Implementation Define and evolve the architecture for our unified data & ML platform: integrating Databricks and AWS services for compute, storage, orchestration, governance and security. Lead hands-on implementation of platform components: infrastructure provisioning (IaC), DevSecOps pipelines, DataOps workflows, ML pipelines and operationalization. Collaborate with internal teams to deliver robust, scalable, secure ML/AI platforms that support multiple markets/environments. 3. Delivery & Enablement Work directly with engineering/data science teams to implement solutions, troubleshoot issues, tune performance and optimize cost. Provide best-practice guidance, documentation, and enablement to stakeholders and internal peer teams (engineering, data science, ops). Monitor solution adoption, drive continuous improvement, and act as the voice of the business stakeholders to internal product/engineering teams. 4. Innovation & Scale Stay ahead of emerging technologies in Databricks, AWS, ML/AI — and translate them into new solution patterns and accelerator frameworks Promote reusable reference architectures, automation templates, observability frameworks and governance guardrails that enable scale and repeatability. Deep technical expertise in Databricks and AWS, including integration of services across both platforms (e.g., Delta Lake, EMR, Glue, S3, SageMaker). Proven hands-on implementation skills: capable of designing and delivering complex systems end to end — infrastructure, data, ML pipelines, monitoring and operations. Experience building scalable ML/AI platforms: ingesting & processing large volumes of data, feature engineering, model training/deployment, monitoring and lifecycle management. Strong programming experience with Python, SQL; familiarity with Spark; experience with IaC (Terraform, CloudFormation), orchestration (Airflow, Databricks Workflows) and container/Kubernetes environments. Stakeholder-facing orientation: ability to engage with both technical and business stakeholders, translate requirements into solutions, and present ideas clearly. Solid understanding of DevSecOps, DataOps, observability, cost-governance and platform reliability best-practices. Excellent communication and collaboration skills; experience working across geographies and in fast-moving, multi-stakeholder environments. Why Join Us Be at the forefront of building the data & AI platform that powers a global digital banking group. Engage with business stakeholders as a technical solution partner — your work directly influences business outcomes. Work with a modern stack: Databricks, AWS, Delta Lake, Spark, MLflow, Terraform, Kubernetes and more. Join a growth-oriented team with autonomy, strong technical leadership and the opportunity to make a real impact. Performance bonus up to 2 months 13th month salary pro-rata 15-day annual leave+ 3-day sick leave + 1 birthday leave + 1 Christmas leave Meal and parking allowance are covered by the company. Full benefits and salary rank during probation. Insurances as Vietnamese labor law and premium health care for you and your family without seniority compulsory SMART goals and clear career opportunities (technical seminar, conference, and career talk) - we focus on your development. Values-driven, international working environment, and agile culture. Overseas travel opportunities for training and working related. Internal Hackathons and company's events (team building, coffee run, blue card...) Work-life balance 40-hr per week from Mon to Fri.

Responsibilities

The Senior Solutions Architect will serve as a trusted advisor to stakeholders, guiding them through their data and AI journeys while designing and implementing high-impact solutions. This role involves architecting end-to-end data and ML solutions on Databricks and AWS, collaborating with internal teams, and ensuring the delivery of robust, scalable platforms.