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Data EngineerSimplifyNext · Singapore
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SimplifyNext

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Data Engineer

🗓️ Posted 2026-09-10 Singapore Hybrid ICT
💰 Salary Not shared 📊 Market S$5,500–S$10,000/mo

About the Company

SimplifyNext is a Singapore-headquartered digital engineering firm, with offices in Thailand and Malaysia, working across three converged areas: agentic AI, AI-enabled application modernisation, and intelligent automation. We bring strong business process consulting together with deep technology skills and modern delivery practices - product-centric, agile and AI-assisted. We build bespoke applications and AI systems, and we go deep on the platforms our clients run on, including Microsoft, AWS, ServiceNow, Databricks and UiPath. That combination of engineering depth and platform depth is what our clients come to us for. We build and modernise the systems people depend on daily. Our 300+ practitioners are multi-disciplinary by design - business consultants, software engineers, architects, AI engineers and designers working on the same delivery, not handing off between silos. We focus on delivering outcomes for clients, building strong careers for our people, and staying ahead of the technology curve. We hire because we are growing. The Data Engineer designs, builds and deploys scalable data lakehouse platforms for our clients - architecting end-to-end pipelines, establishing data quality frameworks, and delivering production-ready solutions that form the foundation of an organisation's data infrastructure. You will work across modern lakehouse stacks (Databricks, Spark, Microsoft Fabric or AWS) alongside architects, AI engineers and business analysts on the same delivery, not in a separate data silo. Design and implement scalable ETL/ELT pipelines on modern cloud data platforms - AWS (Glue, Step Functions, Lambda, S3), Databricks, Spark or Microsoft Fabric. Architect and build data lakehouse solutions using open table formats such as Apache Iceberg, Delta Lake or S3 Tables, including schema evolution, partition evolution and ACID transactions. Optimise pipelines for performance, cost and reliability at enterprise scale. Define, implement and maintain automat

Requirements

  • ● Degree in Computer Science, Data Engineering, Information Systems or a related field.
  • ● 4+ years of hands-on experience in data engineering, ETL/ELT development or data platform roles, building and operating production pipelines.
  • ● Strong hands-on experience with at least one modern data platform - Databricks, Apache Spark, Microsoft Fabric or AWS (Glue, Step Functions, Lambda, S3, Redshift).
  • ● Proficiency with open table formats and lakehouse architecture - Apache Iceberg, Delta Lake or S3 Tables - including schema evolution, partitioning and ACID transactions.
  • ● Strong SQL and proficiency in Python (or Scala/Java) for data processing and automation.
  • ● Experience designing data models and warehouse/lakehouse layers for analytics, reporting and AI workloads.
  • ● Experience defining and automating data quality validation, monitoring and reconciliation.
  • ● Working knowledge of DevOps for data - CI/CD, version control and infrastructure-as-code (Terraform, CloudFormation or equivalent).
  • ● Ability to work directly with business and technical stakeholders and communicate technical designs clearly to non-technical audiences.
  • ● Experience delivering data projects in the Singapore Public Sector, particularly in a Government Commercial Cloud (GCC / GCC+) environment.
  • ● Cloud or platform certification - AWS Certified Data Analytics, AWS Certified Solutions Architect, Databricks Data Engineer, or Azure/Fabric Data Engineer.
  • ● Exposure to AI/ML workloads - feature pipelines, vector stores, RAG data preparation or MLOps.
  • ● Experience with data migration from legacy systems, including reconciliation and cutover.
  • ● Familiarity with governance frameworks and PII handling (e.g. masking, tokenisation, Presidio).
  • ● Experience with BI and semantic layers (Power BI, Tableau, Looker) and enabling self-service analytics.
  • ● You want to work only on ad-hoc analysis and dashboards rather than building and running pipelines.
  • ● You see data quality, testing and documentation as someone else's job.
  • ● You're uncomfortable supporting what you build once it's in production.
  • ● You prefer a single fixed tech stack over learning new platforms as client needs change.
  • ● You treat technical documentation and operational handover as an afterthought.
  • ● Apps, automation, and AI aren't separate teams here - you'll work across all three as one connected practice, not get boxed into a single lane.
  • ● Regardless of platform, every specialist here is AI-enabled by design, powered by our own in-house AI workbench that pairs humans and AI from discovery to testing.
  • ● Tech trends come and go - today's hot platform is tomorrow's afterthought. We multi-skill our people across platforms and AI so your career keeps growing no matter where the market moves.
  • ● Across every platform we work in, our AI-integrated practice is the largest in the region, with work good enough to be cited at Google's own AI event.
  • ● We're one of Singapore's 100 Fastest Growing Companies, expanding fast across Thailand and Malaysia - plenty of room to grow with us.
  • ● At SimplifyNext, we're committed to building a team of curious, driven, and forward-thinking individuals who care deeply about creating meaningful impact through technology. If you're excited by the opportunity to grow, collaborate, and shape the future of digital transformation across the region, we'd be happy to hear from you.