Funding Societies | Modalku Group

• GenAI-Accelerated Security: Research and prototype ways to use Large Language Models (LLMs) and Generative AI to automate threat modelling, triage vulnerability reports, and generate remediation code for developers. • Autonomous Penetration Testing: Assist in evaluating, building, or deploying autonomous Secure AI agents and scripts designed to automate Offensive Security Testing within our test environments. • Secure SDLC Integration: Work alongside security engineers to integrate and tune Static (SAST), Dynamic (DAST), Supply Chain Security and Software Composition Analysis (SCA) tools within our CI/CD pipelines. • Vulnerability Management: Analyse security findings, filter out false positives, and collaborate with software engineers to remediate potential vulnerabilities. • Research & Documentation: Stay up to date on the latest AI-driven attack vectors (e.g., prompt injection, model poisoning) and document internal security guidelines for safe AI adoption.

Role Description We are looking for a highly motivated and curious Product Security Intern. Under the expertise and guidance of our internal security team, you will explore how Generative AI can accelerate security workflows, research autonomous penetration testing frameworks, and help us embed robust Secure Software Development Life Cycle (SDLC) practices directly into our engineering culture. If you are passionate about hacking, building secure software, and interested to learn and build together how to leverage AI to outsmart adversaries, this is the role for you. What You Will Do - GenAI-Accelerated Security: Research and prototype ways to use Large Language Models (LLMs) and Generative AI to automate threat modelling, triage vulnerability reports, and generate remediation code for developers. - Autonomous Penetration Testing: Assist in evaluating, building, or deploying autonomous Secure AI agents and scripts designed to automate Offensive Security Testing within our test environments. - Secure SDLC Integration: Work alongside security engineers to integrate and tune Static (SAST), Dynamic (DAST), Supply Chain Security and Software Composition Analysis (SCA) tools within our CI/CD pipelines. - Vulnerability Management: Analyse security findings, filter out false positives, and collaborate with software engineers to remediate potential vulnerabilities. - Research & Documentation: Stay up to date on the latest AI-driven attack vectors (e.g., prompt injection, model poisoning) and document internal security guidelines for safe AI adoption. Qualifications - Core Security Knowledge: Solid understanding of common vulnerabilities (e.g., OWASP Top 10) and fundamental security concepts (authentication, cryptography, networking). - Programming Skills: Proficiency in at least one programming or scripting language (e.g., Python, Go, JavaScript, or bash) to write automation scripts and interact with APIs. - AI/ML Curiosity: A strong interest in Generative AI, LLMs, and how AI can be applied offensively and defensively in cybersecurity. (Prior experience using LLM APIs like OpenAI, Gemini, or Anthropic is a major plus). - Builder’s Mindset: Familiarity with modern software development stack/tools, version control (Git), and an understanding of basic CI/CD concepts. - Problem Solver: Excellent analytical skills with a proactive approach to tackling complex, ambiguous problems. - Education: Background in Computer Science, Cybersecurity, Information Security, or a related technical field. Benefits - Expert Mentorship & Training: Learn directly from our in-house security experts. You will receive hands-on training on how to secure an organization comprehensively at every layer of the SDLC and beyond. - Strategic Collaboration: Join hands with our security engineers to be an active, contributing member of our GenAI-accelerated security program. - Impact: Your research and code will directly influence how our security team scales its operations. - Flexible working: We believe in giving back the control of work & life to our people. We trust our people and love to provide the space to accommodate each and everyone's working style and personal life. - Mental health and wellness: We understand that our team productivity is directly linked to our mental and physical health. Hence we organize org-wide fitness initiatives and engage partners to provide well-being coaching. - Tech support: We provide a company laptop for our employees and the best possible support for the right equipment/tools to enable high productivity.

• Run recurring and ad-hoc report pulls from dashboards, databases, and analytics tools • Validate data accuracy, investigate anomalies, and flag inconsistencies • Support dashboard updates, fixes, and basic troubleshooting • Perform basic exploratory analysis to help explain trends, changes, or outliers in reports • Translate data outputs into clear, concise summaries for decision-making • Use AI tools to generate and refactor SQL queries • Automate recurring report pulls and summaries • Assist with data validation and QA checks • Help prototype lightweight automations that reduce repetitive analytics work

Role Overview We’re looking for a Data Intern to support analytics operations through reporting and analysis, while experimenting with AI-driven automation to reduce manual effort. This role sits at the intersection of data operations and insight. You’ll work with real world data, help answer real business questions, and learn how analytics teams scale impact.  Key Responsibilities Reporting & Data Support - Run recurring and ad-hoc report pulls from dashboards, databases, and analytics tools - Validate data accuracy, investigate anomalies, and flag inconsistencies - Support dashboard updates, fixes, and basic troubleshooting Analysis & Insight - Perform basic exploratory analysis to help explain trends, changes, or outliers in reports - Translate data outputs into clear, concise summaries for decisionmaking AI & Automation - Use AI tools to: - Generate and refactor SQL queries - Automate recurring report pulls and summaries - Assist with data validation and QA checks - Help prototype lightweight automations that reduce repetitive analytics work

Role Overview We’re looking for a Data Intern to support analytics operations through reporting and analysis, while experimenting with AI-driven automation to reduce manual effort. This role sits at the intersection of data operations and insight. You’ll work with real world data, help answer real business questions, and learn how analytics teams scale impact.  Key Responsibilities Reporting & Data Support - Run recurring and ad-hoc report pulls from dashboards, databases, and analytics tools - Validate data accuracy, investigate anomalies, and flag inconsistencies - Support dashboard updates, fixes, and basic troubleshooting Analysis & Insight - Perform basic exploratory analysis to help explain trends, changes, or outliers in reports - Translate data outputs into clear, concise summaries for decisionmaking AI & Automation - Use AI tools to: - Generate and refactor SQL queries - Automate recurring report pulls and summaries - Assist with data validation and QA checks - Help prototype lightweight automations that reduce repetitive analytics work

Role Overview We’re looking for a Data Intern to support analytics operations through reporting and analysis, while experimenting with AI-driven automation to reduce manual effort. This role sits at the intersection of data operations and insight. You’ll work with real world data, help answer real business questions, and learn how analytics teams scale impact.  Key Responsibilities Reporting & Data Support - Run recurring and ad-hoc report pulls from dashboards, databases, and analytics tools - Validate data accuracy, investigate anomalies, and flag inconsistencies - Support dashboard updates, fixes, and basic troubleshooting Analysis & Insight - Perform basic exploratory analysis to help explain trends, changes, or outliers in reports - Translate data outputs into clear, concise summaries for decisionmaking AI & Automation - Use AI tools to: - Generate and refactor SQL queries - Automate recurring report pulls and summaries - Assist with data validation and QA checks - Help prototype lightweight automations that reduce repetitive analytics work

Role Description We are seeking a passionate Senior Data Engineer for the regional Data Team. This role requires you to design, develop and implement a cloud-based Data Warehouse, architect data ingestion from diverse sources into a central platform, write performant SQL, build and optimize ETL/ELT pipelines with dbt, tune and debug the DWH, and partner closely with Data Analytics, Data Science, and business stakeholders across our Financing and Payments products. As a senior member of the team, you will be expected to lead technical initiatives end-to-end and mentor other engineers. - Design, develop and maintain scalable, production-grade data pipelines and build new API integrations to support growing data volume and complexity across our lending and payments products. - Build and maintain modular, tested, and well-documented data transformation models using dbt on top of Snowflake. - Lead high-impact data platform initiatives end-to-end-- from scoping and technical design through delivery, monitoring, and iteration. - Collaborate with analytics, data science, and business teams to evolve data models that power BI tools, regulatory reporting, and data-driven decision making across the organization. - Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources using SQL, Snowflake, dbt, and AWS big data technologies. - Partner with Executive, Product, Risk, Finance, and Engineering stakeholders to resolve data-related technical issues and support their data infrastructure needs. - Champion data quality, governance, lineage, and cost efficiency across the data platform. - Mentor junior and mid-level data engineers through code reviews, design reviews, and knowledge sharing. Qualifications - Bachelor's or Master's degree in a technical or business discipline, or equivalent practical experience. - 6+ years of hands-on experience managing data platforms, data tools, and/or data management technologies, with demonstrated progression into senior or lead responsibilities. - Prior experience working in Payments, Lending, Banking, or Financial Technology environments, with a solid understanding of financial data concepts (e.g. transactions, ledgers, reconciliation, settlement, disbursement, repayment lifecycles). - Strong grasp of the business context of a Fintech / Financial Technology Platform -- including regulatory reporting needs, data sensitivity, auditability, and how data powers credit, risk, and operations decisions. - Advanced SQL expertise and deep experience with relational databases and query optimization. - Proven experience building and optimizing big data pipelines, architectures, and datasets on Snowflake and AWS (e.g. S3, Glue, Lambda, IAM, MWAA). - Hands-on production experience with dbt (data build tool) -- including model design, testing, documentation, macros, and deployment workflows. - Experience with orchestration tools such as Airflow / MWAA , ideally integrated with dbt in production. - Track record of leading multiple high-impact data projects , from technical design through stakeholder alignment, delivery, and post-launch optimization. - Experience performing root cause analysis on data and processes to answer business questions and identify opportunities for improvement. - Exposure to data visualization tools (Qlik, Tableau, Looker, Metabase, Sisense, etc.). - Familiarity with data warehouse design patterns, dimensional modeling, and data governance practices. - Proficiency in Python (strongly preferred; Java, Scala, or JavaScript also welcome). - Working knowledge of Git/GitHub and JIRA. Requirements - A "build-test-measure-improve" mentality, with the drive to motivate teams and deliver impactful outcomes. - Passion for operational efficiency, quantitative performance metrics, and process orientation. - Strong ownership mindset -- able to drive initiatives independently while keeping stakeholders aligned. - Working knowledge of project planning methodologies, IT standards, and engineering best practices. - Customer passion, business focus, and the ability to negotiate, facilitate, and build consensus across cross-functional teams. - Ability to promote a collaborative team environment across multiple agile squads and regional stakeholders. - Experience with Agile software development methodologies. - Comfortable operating in a regional, multi-country setup across Southeast Asia. Benefits - Time off - We would love you to take time off to rest and rejuvenate. We offer flexible paid vacations as well as many other observed holidays by country. We also like to have our people take a day off for special days like birthdays and work anniversaries. - Flexible working - We believe in giving back the control of work & life to our people. We trust our people and love to provide the space to accommodate each and everyone's working style and personal life. - Medical benefits - We offer health insurance coverage for our employees and dependents. Our people focus on our mission knowing we have their backs for their loved ones too. - Mental health and wellness - We understand that our team productivity is directly linked to our mental and physical health. Hence we organize org-wide fitness initiatives and engage partners to provide well-being coaching. - Tech support - We provide a company laptop for our employees and the best possible support for the right equipment/tools to enable high productivity.

• Design, develop and maintain scalable, production-grade data pipelines and build new API integrations to support growing data volume and complexity across our lending and payments products. • Build and maintain modular, tested, and well-documented data transformation models using dbt on top of Snowflake. • Lead high-impact data platform initiatives end-to-end-- from scoping and technical design through delivery, monitoring, and iteration. • Collaborate with analytics, data science, and business teams to evolve data models that power BI tools, regulatory reporting, and data-driven decision making across the organization. • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources using SQL, Snowflake, dbt, and AWS big data technologies. • Partner with Executive, Product, Risk, Finance, and Engineering stakeholders to resolve data-related technical issues and support their data infrastructure needs. • Champion data quality, governance, lineage, and cost efficiency across the data platform. • Mentor junior and mid-level data engineers through code reviews, design reviews, and knowledge sharing.

Funding Societies | Modalku is the largest SME digital finance platform in Southeast Asia. We are licensed and operating  in Singapore, Indonesia, Thailand, Malaysia and Vietnam, and backed by Sequoia India (Peak XV), Softbank Vision Fund, Khazanah and SMBC bank amongst many others. Funding Societies | Modalku provides business financing to small and medium-sized enterprises (SMEs), which is funded by individual and institutional investors, as well as payments solutions to SMEs and consumers. Here at Funding Societies | Modalku we live by our core values GETFS: - Grow Relentlessly: Strive to become our best, most authentic selves. - Enable Teamwork, Disable Politics: Only by forging togetherness, we help each other succeed. - Test Measure Act: Stay curious and reinvent ourselves, through innovation and experimentation. - Focus on Impact: Create impact through bias for action and tangible results. - Serve with Obsession: Build win-win relationships for the long-term by having a customer obsession. We are seeking a passionate **Senior Data Engineer** for the regional Data Team. This role requires you to design, develop and implement a cloud-based Data Warehouse, architect data ingestion from diverse sources into a central platform, write performant SQL, build and optimize ETL/ELT pipelines with dbt, tune and debug the DWH, and partner closely with Data Analytics, Data Science, and business stakeholders across our Financing and Payments products. As a senior member of the team, you will be expected to lead technical initiatives end-to-end and mentor other engineers. What you will do: - Design, develop and maintain scalable, production-grade data pipelines and build new API integrations to support growing data volume and complexity across our lending and payments products. - Build and maintain modular, tested, and well-documented data transformation models using **dbt** on top of Snowflake. - Lead high-impact data platform initiatives end-to-end-- from scoping and technical design through delivery, monitoring, and iteration. - Collaborate with analytics, data science, and business teams to evolve data models that power BI tools, regulatory reporting, and data-driven decision making across the organization. - Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources using SQL, Snowflake, dbt, and AWS big data technologies. - Partner with Executive, Product, Risk, Finance, and Engineering stakeholders to resolve data-related technical issues and support their data infrastructure needs. - Champion data quality, governance, lineage, and cost efficiency across the data platform. - Mentor junior and mid-level data engineers through code reviews, design reviews, and knowledge sharing.

Funding Societies | Modalku is the largest SME digital finance platform in Southeast Asia. We are licensed and operating  in Singapore, Indonesia, Thailand, Malaysia and Vietnam, and backed by Sequoia India (Peak XV), Softbank Vision Fund, Khazanah and SMBC bank amongst many others. Funding Societies | Modalku provides business financing to small and medium-sized enterprises (SMEs), which is funded by individual and institutional investors, as well as payments solutions to SMEs and consumers. Here at Funding Societies | Modalku we live by our core values GETFS: - Grow Relentlessly: Strive to become our best, most authentic selves. - Enable Teamwork, Disable Politics: Only by forging togetherness, we help each other succeed. - Test Measure Act: Stay curious and reinvent ourselves, through innovation and experimentation. - Focus on Impact: Create impact through bias for action and tangible results. - Serve with Obsession: Build win-win relationships for the long-term by having a customer obsession. We are seeking a passionate **Senior Data Engineer** for the regional Data Team. This role requires you to design, develop and implement a cloud-based Data Warehouse, architect data ingestion from diverse sources into a central platform, write performant SQL, build and optimize ETL/ELT pipelines with dbt, tune and debug the DWH, and partner closely with Data Analytics, Data Science, and business stakeholders across our Financing and Payments products. As a senior member of the team, you will be expected to lead technical initiatives end-to-end and mentor other engineers. What you will do: - Design, develop and maintain scalable, production-grade data pipelines and build new API integrations to support growing data volume and complexity across our lending and payments products. - Build and maintain modular, tested, and well-documented data transformation models using **dbt** on top of Snowflake. - Lead high-impact data platform initiatives end-to-end-- from scoping and technical design through delivery, monitoring, and iteration. - Collaborate with analytics, data science, and business teams to evolve data models that power BI tools, regulatory reporting, and data-driven decision making across the organization. - Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources using SQL, Snowflake, dbt, and AWS big data technologies. - Partner with Executive, Product, Risk, Finance, and Engineering stakeholders to resolve data-related technical issues and support their data infrastructure needs. - Champion data quality, governance, lineage, and cost efficiency across the data platform. - Mentor junior and mid-level data engineers through code reviews, design reviews, and knowledge sharing.