or apply directly on SimplifyNext's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 7 days SimplifyNext's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 0% of SimplifyNext's roles list one
- Ghost-job risk at SimplifyNext
- high 31 stale, 1 reposted of 33 open
- Hiring momentum
- 33 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from SimplifyNext's own greenhouse board since 2026-08-03. Full hiring picture for SimplifyNext.
About this role
As a Data Engineer at SimplifyNext, you will design, build, and deploy scalable data lakehouse platforms for clients, focusing on end-to-end data pipelines and data quality frameworks. You will collaborate with cross-functional teams to implement ETL/ELT processes on modern cloud platforms, ensuring data governance and supporting analytics teams. Your role will also involve writing production-quality code, applying DevOps practices, and using AI tools to enhance delivery efficiency.
- benefits
- 1/5
- freshness
- 5/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of SimplifyNext as an employer.
What you need
- 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.
Nice to have
- 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).
Worth weighing
- No salary or benefits information provided.
- The role requires ongoing support for production systems, which may not appeal to everyone.
- Candidates should be open to learning new platforms as client needs change, rather than sticking to a single tech stack.
- Emphasis on technical documentation and operational handover may not suit those who prefer less structured roles.
Summarised from SimplifyNext's posting. Read the full original.
Listed by SimplifyNext on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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