Tyme

Data Engineer

• Design, develop, test, deploy and monitor data pipelines in Databricks on AWS from a wide variety of data sources.
• Design, develop, test, deploy and monitor scalable code with PySpark and SQL in Databricks.
• Identify opportunities to improve internal process through code optimisation and automation.
• Build data quality dashboards, lineage flows / and or monitoring tools to utilize the data pipeline, providing active monitoring and actionable insight into overall data quality and data governance.
• Assist in migrating data from legacy systems onto newly developed solutions.
• Follow and lead best practices on all data security, retention, and privacy policies.

Data Engineer – Lending

QA Engineer

• Manage and drive QA excellence in the scrum teams.
• Work closely with other QAs, engineers, analysts and product owners to identify testing areas across deliverables.
• Oversee the creation and execution of test plans and testing strategy for the scrum teams.
• Liaise with Engineering managers and leads for overall end-to-end testing plan and ensure quality releases from Non-Prod environments to Production.
• Lead the automation testing efforts and liaise with other QA leads for reusable QA frameworks.
• Communicate status, risks and issues to senior management and team members.
• Drive QA process and standards changes for high-performing teams.
• Recruiting, training and coaching QA engineers.
• People management for up to 10 QA engineers.
• Build quality culture for both QA team and feature product team.
• Accountable for industry testing, collaborating with QA team in local bank and 3rd party.

Quality Assurance Lead – QA QC, Tester, English

Recruitment

• Proactively source tech talents across Engineering, Product, and Data roles using:
• LinkedIn, GitHub, StackOverflow, Facebook tech communities
• ITViec, ATS database (Workable), and other creative sourcing channels
• Build and maintain high-quality, reusable talent pools for priority roles.
• Design and execute personalized outreach campaigns with strong response rates.
• Conduct talent market research & mapping (availability, competitiveness, skill trends).
• Continuously experiment with new sourcing techniques to improve pipeline quality and speed.
• Screen CVs against well-defined hiring criteria and tech requirements.
• Conduct pre-screen calls using structured checklists (motivation, tech exposure, fit).
• Coordinate interview scheduling efficiently with Hiring Managers and candidates.
• Track candidates accurately in ATS and ensure smooth candidate experience.
• Support recruitment marketing activities:
• Job postings
• Content optimization
• Candidate funnel tracking and reporting

Tech Talent Sourcer – In-house

Scrum Master

• Are you a **technical** **scrum master** that can still code and test when your team requires it?
• Do you have an experience in **product development **and a desire to **build** **high-performing teams**?
• You will be joining a project which talented software engineers in our Digital Bank Build team who is responsible for designing, building, and maintaining the new digital banking platform and the customer channels.
• As part of the team, you will be responsible for implementing software features, involve in technical designs, and writing tests to ensure the high-quality delivery of the product.
• Scrum Masters are expected to do this by setting the pace for delivery and being proactive in planning and forecasting upcoming deliverables.
• To be successful in the role you should demonstrate pragmatism in your approach and be sensitive to the environment that we operate in, using your skills and knowledge to appropriately influence the delivery approach.

Technical Scrum Master

• Are you a **technical** **scrum master** that can still code and test when your team requires it? Do you have an experience in **product development **and a desire to **build** **high-performing teams**? If so read on.
• Our team is responsible for creating a brand of new digital financial platforms and apps that are highly reliable and scalable using modern engineering practices.
• You will be joining a project which talented software engineers in our Digital Bank Build team who is responsible for designing, building, and maintaining the new digital banking platform and the customer channels.
• As part of the team, you will be responsible for implementing software features, involve in technical designs, and writing tests to ensure the high-quality delivery of the product.
• The teams operate in Scrum and DevOps models.
• We’re looking for top engineers out there! During the interview process, we will test your coding and design skills to assess your experience and depth of knowledge. Don’t worry our interview process will be fun!
• We are looking for an experienced and versatile **Technical Scrum Master **who will be responsible for building a new scrum team for the delivery of one of our new fintech products.
• **Technical Scrum Master’s **critical responsibility is for the team and for optimal flow of work to DONE. Scrum Masters are expected to do this by setting the pace for delivery and being proactive in planning and forecasting upcoming deliverables. To be successful in the role you should demonstrate pragmatism in your approach and be sensitive to the environment that we operate in, using your skills and knowledge to appropriately influence the delivery approach.

Technical Scrum Master – HCM

Engineering Manager

• Drive and coach Agile teams to deliver on engineering standards, sprint backlogs and plans, engineers’ responsibilities and performance management, code quality, adherence to development guardrails, and testing.
• Drive the execution and delivery of engineering goals by collaborating with many cross-functional teams, architects, and product managers.
• Drive technology roadmap.
• Be a part of the overall architecture and key components design for the current and future framework.
• Be the voice of reason between speed and quality.
• Coach engineers to be T-shaped, versatile, and take responsibility outside their core disciple.
• Own remediation of technical debt.
• Keep up-to-date with modern development technologies and methodologies.
• Be responsible for the full life-cycle development process and the deliveries of a team.
• Empower the product engineering team to be self-sufficient and disciplined.
• Lead initiatives for implementing efficient development and delivery processes.
• Motivate the product team to go above and beyond with continuous delivery and innovation.
• Execute and update the career path development for engineering team members, working with the HR department.

• Drive and coach Agile teams to deliver on engineering standards, sprint backlogs and plans, engineers’ responsibilities and performance management, code quality, adherence to development guardrails, and testing;
• Drive the execution and delivery of engineering goals by collaborating with many cross-functional teams, architects, and product managers;
• Drive technology roadmap;
• Be a part of the overall architecture and key components design for the current and future framework;
• Be the voice of reason between speed and quality;
• Coach engineers to be T-shaped, versatile, and take responsibility outside their core disciple;
• Own remediation of technical debt;
• Keep up-to-date with modern development technologies and methodologies;
• Be responsible for the full life-cycle development process and the deliveries of a team;
• Empower the product engineering team to be self-sufficient and disciplined;
• Lead initiatives for implementing efficient development and delivery processes;
• Motivate the product team to go above and beyond with continuous delivery and innovation;
• Execute and update the career path development for engineering team members, working with the HR department;

Engineering Manager – Investment and Insurance

• This role focused on** data engineering teams** with data warehousing, streaming and batch patterns, CI/CD for data pipelines,
• - Drive and coach Agile teams to deliver on engineering standards, sprint backlogs and plans, engineers’ responsibilities and performance management, code quality, adherence to development guardrails, and testing;
• - Drive Agile delivery across data platforms, ensuring high standards for; Data quality and testing, Code quality and review practices, CI/CD for data pipelines, Documentation and operational readiness
• - Collaborate closely with data architects, product managers, analytics teams, platform teams, and governance stakeholders to deliver data capabilities aligned with business priorities
• - Own the execution of the data engineering roadmap, balancing short-term delivery with long-term platform sustainability
• - Contribute to data platform architecture and design, including ingestion, transformation, storage, and consumption layers
• - Coach engineers to be T-shaped, capable of working across batch, streaming, analytics engineering, and platform concerns
• - Own and prioritise the remediation of technical and data debt, including legacy pipelines, performance issues, and data quality gaps
• - Stay current with modern data engineering tools, patterns, and methodologies, particularly within the Databricks ecosystem
• - Be accountable for the full lifecycle of data solutions, from design through build, deployment, monitoring, and support
• - Empower teams to be self-sufficient, disciplined, and accountable for the reliability of data products
• - Lead initiatives to improve data delivery processes, including automation, observability, and operational excellence
• - Motivate teams to continuously improve through innovation, experimentation, and continuous delivery
• - Drive career development and progression for data engineers, partnering with HR on performance management and growth paths

Engineering Manager – Data Platform

• Focussed on data engineering teams with data warehousing, streaming and batch patterns, CI/CD for data pipelines,
• Drive and coach Agile teams to deliver on engineering standards, sprint backlogs and plans, engineers’ responsibilities and performance management, code quality, adherence to development guardrails, and testing;
• Drive Agile delivery across data platforms, ensuring high standards for Data quality and testing, Code quality and review practices, CI/CD for data pipelines, Documentation and operational readiness
• Collaborate closely with data architects, product managers, analytics teams, platform teams, and governance stakeholders to deliver data capabilities aligned with business priorities
• Own the execution of the data engineering roadmap, balancing short-term delivery with long-term platform sustainability
• Contribute to data platform architecture and design, including ingestion, transformation, storage, and consumption layers
• Coach engineers to be T-shaped, capable of working across batch, streaming, analytics engineering, and platform concerns
• Own and prioritise the remediation of technical and data debt, including legacy pipelines, performance issues, and data quality gaps
• Stay current with modern data engineering tools, patterns, and methodologies, particularly within the Databricks ecosystem
• Be accountable for the full lifecycle of data solutions, from design through build, deployment, monitoring, and support
• Empower teams to be self-sufficient, disciplined, and accountable for the reliability of data products
• Lead initiatives to improve data delivery processes, including automation, observability, and operational excellence
• Motivate teams to continuously improve through innovation, experimentation, and continuous delivery
• Drive career development and progression for data engineers, partnering with HR on performance management and growth paths

Engineering Manager – Data

Solutions Engineer

• Design, evaluate, consult, and deploy end-to-end Customer Service Experience solutions, including omnichannel platforms (chat, voice, in-app messaging, email), case management systems, workflow engines, and customer engagement tools that ensure scalability, resilience, and high availability.
• Architect API-first and event-driven integrations between customer service platforms and core banking systems, CRM, identity systems, and operational platforms to deliver seamless customer journeys.
• Design and implement AI-driven customer service capabilities such as conversational bots, agent assist, case classification, summarisation, and knowledge retrieval while ensuring security, privacy, and responsible AI usage.
• Define scalable case lifecycle, SLA management, escalation, and automation strategies to reduce manual effort and improve first-contact resolution.
• Ensure customer service platforms meet non-functional requirements including performance, reliability, availability, and observability. Proactively identify architecture improvements to optimise cost-to-serve and system efficiency.
• Implement architecture patterns that ensure data protection, access control, auditability, and compliance with banking and regulatory requirements across customer-facing and internal systems.
• Work closely with Customer Experience, Operations, Product, Engineering, Data, and Security teams to translate business needs into clear, actionable solution designs.
• Provide architectural guidance, troubleshoot complex platform issues, and stay updated with industry trends, AI advancements, and best practices in customer service technology.

Solution Architect – Customer Service Experience

Data Scientist

• **What you'll do:**
• As a Data Scientist, you'll work across the full data science lifecycle, from exploration and modeling to production deployment and continuous optimization, turning raw financial data into actionable intelligence that drives customer experiences.
• You will:
• - Collect, structure, clean, and analyze large datasets using the latest statistical tools and techniques, understanding the human and financial behaviors the data represents.
• - Develop statistical models and algorithms to predict trends, behaviors, and patterns in customer financial data.
• - Build machine learning models for various use cases across the organization to predict customer behavior, identify opportunities, and drive business outcomes.
• - Develop and implement creative ways of displaying and disseminating insights, bringing the consumer and data to life in a manner that engages all stakeholders.
• - Use research and insight to drive cultural change within the organization, ensuring stakeholders put consumers at the heart of their planning and strategic thinking.
• - Deliver ad hoc consumer insight projects that inform decision making for management and collaborate with internal teams to identify business problems and provide data-driven solutions.
• - Interpret and analyze data from multiple sources, providing key analytics and proactively recommending actionable next steps across various stakeholders and teams.
• - Think strategically and communicate creatively to inform and drive stakeholder decision making.
• - Effectively use business data from multiple sources to craft compelling stories that guide activities and decisions.

• Build and optimize data ingestion pipelines using Python and PySpark to collect and transform data from multiple sources (transactions, KYC, AML, authentication, devices, logs, etc.).
• **Proficiency in SQL (PostGres preferred) **
• **Design and maintain data model that support Financial Crime/Fraud detection, profiling, and entity resolution. **
• **Implement data quality checks and ensure data reliability across environments.
• **Collaborate closely with Data Scientists, Analysts, Compliance, Operations and our Product/Feature teams to operationalize models and rules. **
• Utilize jobs, workflows, APIs and streaming to manage large-scale data processing workloads.
• Integrate with external systems (e.g. sanctions, ID&V, biometrics and authentication systems) to enrich risk and identity data.
• Support **automation and monitoring** of ETL processes to improve operational efficiency.

Senior Data Engineer – Financial Crime

• Design and implement **graph data models** that represent complex relationships between customers, organizations, transactions, devices, behaviour and events.
• Build **graph data pipelines** to extract, transform, and load (ETL) data from multiple internal and external sources.
• Develop efficient **queries and Graph Data Science algorithms** to support entity resolution, link analysis, and investigative insights.
• Work with graph visualization tools to build intuitive investigation tools for investigators and analysts.
• Collaborate with **Financial Crime/Fraud analysts** to translate investigation use cases into graph-driven solutions.
• Optimize data performance and ensure data quality across graph structures.
• Partner with software engineers and data scientists to integrate graph data into wider Financial Crime/Fraud workflows and detection logic.