Data and AI Engineer

Company Description

ESGpedia is Asia's leading ESG data and technology company, headquartered in Singapore. We offer a comprehensive suite of digital solutions on our one-stop platform to empower corporates, SMEs, and the financial sector to achieve ESG excellence.

The ESGpedia platform powers key initiatives across the Asia Pacific region, including the ESCAP Sustainable Business Network (ESBN) Asia-Pacific Green Deal digital platform and the Asia-Pacific Single Accesspoint for ESG Data (SAFE) initiative. ESGpedia is GRI-licensed.

At ESGpedia, we believe people are our greatest asset. Unified by a common purpose of accelerating the world's transition towards a net zero economy, our team is built on mutual trust, respect, and support. We believe in hands-on learning and taking ownership of one's work – which means creating a spirited environment for all team members to take on exciting challenges, create meaningful impact for our planet, and grow both personally and professionally.

For more information about ESGpedia, please visit: www.esgpedia.io

Job Summary

As a Data and AI Engineer at ESGpedia, you will bring data engineering, customer analytics and applied AI development into one role. You will own assigned solutions from understanding the business question and collecting data through pipelines, dashboards and AI features, including ongoing support. Your work will help customers use accurate sustainability data and help ESGpedia develop reusable products.

Job Responsibilities

• Build reliable, robust and scalable real-time data pipelines. Work with backend engineers to understand data structures, agree on source data contracts and manage schema changes. Build streaming and event-driven ingestion and transformation pipelines, with batch processing where appropriate. Implement validation, monitoring, retries and backfills to keep data accurate and available.


• Deliver Customer Analytics with various Stakeholders. Work with customers, Sales, Product and other stakeholders to clarify needs and define metrics. Analyse data, investigate discrepancies and explain findings. Build and maintain bespoke and common Business Intelligence Dashboards, validating the complete path from source data to displayed results.


• Lead the development of AI Products. Identify opportunities and own delivery from feasibility and prototypes to customer demonstrations and production features. Develop extraction, search, analysis and automation solutions using Databricks and AI services. Evaluate accuracy, cost and latency, and work with application engineers on integration, deployment and monitoring.


• Collect and prepare trusted data. Maintain data collection from databases, APIs, files and public sources, including scraping pipelines. Clean, standardise and reconcile data; resolve duplicates and inconsistent formats; and retain source references. Validate units, reporting periods and missing or revised values with the relevant business owners.


• Build reusable data models and self service analytics. Design analytical datasets and shared metric definitions for dashboards and AI applications. Optimise storage, transformations and queries for performance. Turn repeated customer requirements into reusable models and templates, and evaluate Genie or equivalent tools for customer self-service using governed data and tested answers.


• Maintain service quality and client continuity. Continue supporting existing clients and their Business Intelligence Dashboards while introducing new capabilities. Resolve pipeline and dashboard incidents, preserve the last valid dataset when refreshes fail, and improve freshness and loading performance. Apply testing, code review, version control, CI/CD and customer access controls.


• Own delivery and share knowledge. Estimate work, agree priorities with stakeholders and communicate progress, dependencies and risks. Document calculations, data models, pipelines and support procedures. Provide customer demonstrations and maintain backup coverage so the team can support solutions across data, analytics and AI.

Requirement

• Typically three or more years of relevant experience delivering and supporting data pipelines, analytical solutions or data-driven applications.


• A bachelor's or master's degree in Computer Science, Data Science, Engineering or a related discipline, or equivalent practical experience.


• Strong Python and SQL skills, with the ability to read, improve and troubleshoot existing code.


• Practical understanding of data cleaning, validation, modeling and relational or NoSQL databases, with experience in systems such as MongoDB, MariaDB, MySQL or Redis.


• Ability to translate business questions into analysis, validate calculations and explain results clearly, with experience creating Business Intelligence Dashboards.


• Experience delivering and supporting a production pipeline, dashboard or application, together with working knowledge of testing, Git and structured deployment practices.


• Strong communication, problem-solving and ownership, including stakeholder collaboration and managing changing priorities in a startup.


• Experience with streaming, event-driven systems and schema change management is an advantage.


• Familiarity with Databricks, PySpark, AWS, AI development and evaluation, or self-service analytics tools is a plus.

What We Look For

Self-Starters: You don’t wait for instruction—you spot what needs doing and take initiative. We love that.

Curious Builders: You ask the right questions, dig deep, and thrive in ambiguity. You turn complex problems into elegant, real-world solutions.

Communicators Who Connect: Whether you're writing a report or leading a meeting, you convey your ideas with clarity, empathy, and purpose.

Accountable High Performers: You take ownership, deliver under pressure, and hold yourself to a high standard—even when no one’s watching.

Passion for Impact: You're not just looking for a job—you want to do work that matters. Whether it’s advancing sustainability, transforming client outcomes, or innovating with tech, you're fueled by purpose and driven to make a difference!

ESGpedia is proud to be an equal opportunity workplace for all. We do not discriminate in recruitment, hiring, training, advancement, or other employment practices. We celebrate diversity and are committed to creating and fostering an inclusive environment for all employees.

Notice

We regret to inform that only shortlisted applicants will be notified. All applications will be treated with strictest confidence.

By submitting any application or resume to us, you will be deemed to have read and agreed to the terms of our Privacy Policy (www.esgpedia.io/privacy-policy/), and consented to us collecting, using, retaining and disclosing your personal information to prospective employers for their consideration.

You may refer and access our website(www.esgpedia.io) for more information.