SalaryPeak

Data Engineer

ITCAN PTE. LIMITED
Singapore 3+ years Posted Apr 9, 2026

Salary Range

SGD 78,000 - SGD 120,000 /year

SGD 6,500 - SGD 10,000/month

Skills Required

RDSApache SparkData CleaningIAMData PipelineAWSCost ManagementData GovernanceData EngineeringEMR3-tier, architectureS3Performance ManagementAmazon VPC

Job Description

For asuccessful POC, the candidate should ideally be a Mid-to-Senior level DataEngineer (3–5+ years) with the following "must-haves":

TechnicalCore

  • Databricks Mastery: Expert-level knowledge of Delta Lake and the Medallion Architecture (Bronze/Silver/Gold layers).
  • Apache Spark (PySpark/SQL): Ability to write optimized Spark code. For coming POC, Python is usually preferred over Scala/R for its flexibility and ecosystem.
  • AWS Infrastructure: Deep understanding of S3 (Bucket policies/storage), IAM (Roles/Policies) for secure Databricks access, and VPC/Networking (Good to have)
  • Data Ingestion: Experience with Databricks Autoloader or Unity Catalog for managed data governance.

"POC-Specific"Skills

  • Prototyping Speed: The ability to set up a working end-to-end pipeline (Source → S3 → Databricks → OOTB BI Tool) in weeks, not months.
  • Cost Management: Knowledge of how to configure Databricks Clusters (Autoscaling, Spot Instances) to prevent the POC from blowing your AWS budget.

JobDescriptions

Focus: Hands-on ETL/ELT and connectingvarious data sources and setup the platform with technical leadership.

  • Role Summary:
  • We are seeking a hands-on Data Engineer to spearhead our Databricks POC on AWS. You will be responsible for the initial environment setup, security configuration, and designing the framework for our future data platform.
  • You will connect diverse AWS and external data sources into a unified Databricks environment.
  • Key Responsibilities:
  • Configure Databricks workspace integration with AWS (S3, IAM, VPC).
  • Cleanse and transform raw data from S3, RDS, and APIs into Delta tables.
  • Design and implement a scalable Medallion Architecture using Delta Lake.
  • Build automated ingestion pipelines using Databricks Autoloader.
  • Optimize Spark jobs for performance and reliability.
  • Establish data governance standards using Unity Catalog. (Good to have)
  • Evaluate POC success metrics (performance, cost, ease of use).
  • Requirements: 3-5+ years in Data Engineering with PySpark/SQL; strong experience with AWS Glue or EMR is a plus.; Databricks Certified Data Engineer Professional preferred.