A company near Raffles Place is hiring an Associate Hadoop Developer, full-time and on-site, at SGD 8,500 a month. This role expects 18 months of hands-on experience with data pipelines, making it a reasonable next step for someone past their first year in a data role but not yet operating at a senior level. The team behind this hire supports a handful of internal business units, so the pipelines built here feed directly into decisions rather than sitting in a research or experimental capacity.
Education and experience
A bachelor's degree is required, and while the field isn't rigidly specified, most candidates come from computer science, information systems, or a similarly technical background. The role is calibrated around 18 months of practical experience with data pipelines, ideally including direct exposure to the Hadoop ecosystem rather than only relational databases. Candidates without that specific exposure but with strong SQL fundamentals and a genuine interest in distributed systems are still worth a conversation. What matters more than a checklist of tools is whether you can reason clearly about where data actually lives and how it moves, since the specific technology stack can be picked up faster than that underlying instinct.
What the job involves
- Design and maintain data pipelines that move information reliably between systems
- Integrate data from multiple source systems into a consistent, usable format
- Build reports and dashboards that business teams actually rely on for decisions
- Check data quality at each stage, since a broken pipeline upstream quietly corrupts everything downstream
A recent project on this team involved reconciling sales figures coming from three regional systems that each recorded currency conversions slightly differently. The fix wasn't complicated once found, but finding it took careful, patient tracing through each pipeline stage. That kind of detective work comes up more than the job title suggests. It's rarely dramatic, mostly a matter of checking assumptions one at a time until the mismatch reveals itself, but it's satisfying work once the pattern clicks into place. Anyone who's enjoyed untangling a stubborn spreadsheet formula error will recognize the rhythm of it.
Core and nice-to-have skills
Hadoop, HDFS, and MapReduce form the technical backbone of the role, alongside Hive for querying and SQL for the more conventional data work that still makes up a real portion of the job. Data pipeline experience ties it all together. Many candidates coming from a purely SQL background underestimate how much this role still relies on that skill day-to-day, even within a Hadoop-centric stack.
- Hadoop, HDFS, and MapReduce fundamentals
- Hive for querying large datasets
- SQL, comfortable enough for both simple lookups and more complex joins
- Experience building or maintaining data pipelines end to end
Beyond the core set, familiarity with Spark speeds up much of the processing work this ecosystem still relies on heavily, and exposure to Sqoop or Oozie for moving data in and out of Hadoop or scheduling jobs is useful but not mandatory. Some comfort with a BI tool like Tableau or Power BI helps too, since the reporting side of the role sits closer to business stakeholders than the pipeline work does. None of these are required on day one. The team would rather hire for solid fundamentals and teach the specific tooling than the reverse.
Team setup
The data engineering team here is small, four people covering both pipeline work and the BI reporting that depends on it, so the line between the two blurs more than it might at a larger company. One of the senior engineers on the team was hired through Naukri Mitra a couple of years back and has since become the informal go-to for anyone new getting oriented with the codebase. Expect a fair amount of direct collaboration with the business teams who consume these reports, since their questions about a number usually land directly on the engineer who built the pipeline behind it. That direct exposure to non-technical stakeholders is genuinely useful for anyone hoping to move into a more senior data role eventually, since explaining a pipeline's limitations to someone who isn't technical is a skill in itself.
Some weeks lean heavily toward pipeline development, others toward firefighting a data quality issue that surfaced in a dashboard someone was actively presenting from. Both are a normal part of the role, not a sign something's gone wrong. There's a weekly sync where the whole team reviews anything that broke in the past week, which is often the most useful hour for a newer engineer to learn how the existing pipelines fit together.
Compensation and benefits
- Salary of SGD 8,500 per month
- Health insurance
- Paid time off
- Professional development support, including budget toward relevant courses or certifications
- Statutory CPF retirement contributions and annual leave in line with Singapore employment standards
Anyone tracking Hadoop developer salary in Singapore per month will find this sits in a fair range for an associate-level position in the Central Region, particularly given the professional development support attached. That support has historically gone toward Hadoop ecosystem certifications or targeted Spark training, based on what previous hires in this role have actually used it for.
Applying
This is an on-site role based near Raffles Place, so candidates should be able to commute to the Central Region regularly. Send a resume that highlights specific pipelines or data integration projects you've worked on, along with the scale of data involved where you can estimate it. A rough sense of daily data volume or the number of source systems you've integrated gives the hiring team something concrete to evaluate, more useful than a general list of tools without that context. For those tracking Hadoop developer job openings in Singapore more broadly, this one moves relatively quickly, with a single technical round covering SQL and a walkthrough of a past pipeline project, followed by a short conversation with the hiring manager. Most candidates hear back within a week of the final interview, and the team has generally been willing to work around a reasonable notice period for candidates coming from another role.
