🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Activate Interactive Pte Ltd (“Activate”) is a leading technology consultancy headquartered in Singapore with a presence in Malaysia and Indonesia. Our clients are empowered with quality, cost-effective, and impactful end-to-end application development, like mobile and web applications, and cloud technology that remove technology roadblocks and increase their business efficiency. We believe in positively impacting the lives of people around us and the environment we live in through the use of technology. Hence, we are committed to providing a conducive environment for all employees to realise their full potential, who in turn have the opportunity to continuously drive innovation. We are searching for our next team members to join our growing team. If you love the idea of being part of a growing company with exciting prospects in mobile and web technologies that create positive impact on people’s lives, then we would love to hear from you. Co-Development Business Unit is looking for Data Engineer (Data Engineering & Analytics) This is a 1 - year contract role. Internal Code: A26321 Digital Excellence & Products Division (DXD) is a GovTech team within the Ministry of Education (MOE). DXD sits at the intersection of technology, design, and education, building meaningful products, platforms, and digital services that improve teaching, learning, school operations, and the experience of students, teachers, and school leaders. We are looking for a DevSecOps & Engineering Enablement Engineer to establish and operate a consistent, secure, and reliable process for moving code from development to production for the future SSOE platform. You will centrally manage the tools, pipelines, standards, and automation that engineering teams use to build, test, review, secure, and deploy their code. The objective is to ensure that code progressing towards production is not only deployed successfully, but is also functionally working, secure, tested, and of the required quality. Relevant security, testing, and quality gates should be built directly into the delivery process and applied consistently across engineering teams. You will also drive the responsible use of AI within the software development lifecycle, including AI-assisted code review, testing, security analysis, documentation, and engineering feedback. What will you do? As a Data Engineering & Analytics Engineer, you will own the data lifecycle from source systems through ingestion, transformation, modelling, quality, and serving. You will build pipelines that extract and ingest data from enterprise and operational systems, transform it into consistent and trusted datasets, and make that data available to applications, dashboards, reporting, analytics, and machine-learning use cases. You will work closely with the Logging & Data Platform Engineer on shared platform capabilities and with Software Engineers and other consumers to define reliable data interfaces and products. Data Pipeline Engineering Design, build, and operate production-grade data pipelines for data extraction, ingestion, transformation, and loading (ETL/ELT) Integrate data from on-premises systems, enterprise applications, APIs, databases, SaaS platforms, files, streams, cloud services, and other operational data sources Develop batch, incremental, change-data-capture (CDC), streaming, and event-driven ingestion patterns based on source-system and business requirements Build transformation pipelines that clean, enrich, standardise, join, aggregate, and structure raw data into trusted datasets Design secure and resilient mechanisms for transferring and synchronising data between on-premises, GCC, AWS, Azure, and other approved environments Design pipelines for failure handling, retry, recovery, idempotency, scalability, and changing data volumes Automate pipeline deployment, configuration, testing, and operation Data Architecture & Modelling Design and maintain cloud-native and hybrid data stores, data lakes, and analytical datasets Develop data models that provide consistent representations of enterprise, operational, and asset information Define schemas and data contracts between data producers and downstream consumers Design data structures appropriate for operational applications, reporting, analytics, and machine-learning workloads Apply backwards-compatible schema changes and coordinate changes that may affect downstream consumers Maintain data lineage and metadata so datasets are traceable and discoverable Work with platform and application teams to define appropriate data-serving and integration patterns Data Quality & Reliability Implement automated data validation, reconciliation, completeness, consistency, and quality controls throughout the pipeline lifecycle Monitor data freshness, pipeline health, processing latency, and data-quality indicators Detect and investigate ingestion failures, source-system changes, data-quality anomalies, and reconciliation differences Prevent invalid or incomplete data from silently propagating to downstream consumers Define appropriate SLOs for data freshness, availability, and pipeline reliability Build monitoring, alerting, error handling, and recovery into data pipelines from the outset Analytics & Data Products Build trusted datasets and reusable data products for applications, dashboards, operational reporting, and analytics Develop datasets supporting asset intelligence, operational visibility, capacity planning, trend analysis, and decision-making Enable advanced analytics and machine-learning use cases using cloud-native data, analytics, and AI/ML capabilities Work with users and stakeholders to translate operational questions into appropriate datasets, metrics, and analytical products Support exploratory analysis and prototyping where required before operationalising successful approaches Ensure analytical outputs are based on governed, traceable, and reproducible data Data Integration Design data architectures spanning on-premise infrastructure and cloud platforms Integrate traditional enterprise systems with modern cloud-native data capabilities Design for connectivity constraints, network boundaries, security zones, and data-residency requirements Implement appropriate buffering, checkpointing, retry, and reconciliation where data crosses environment boundaries Select appropriate integration patterns based on data volume, latency, source-system capability, and operational requirements Work with infrastructure, network, security, and platform teams to establish secure data flows Security & Governance Ensure data is collected, transmitted, stored, processed, and accessed according to applicable security requirements Enforce appropriate access controls and least-privilege principles for data platforms and pipelines Ensure sensitive information is appropriately classified and protected throughout the data lifecycle Maintain auditability and traceability of data-processing activities Apply retention, archival, lifecycle, and deletion requirements to data products Participate in security, architecture, data-governance, and operational-readiness reviews Reliability & Operations Operate and support production data pipelines and data products Participate in operational support and on-call responsibilities for owned services Investigate p
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
