Data Engineer/Senior Data engineer-Python, PySpark, SQL, Databricks

Rapsys Technologies Pte Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Rapsys Technologies Pte Ltd. is seeking a skilled Data Engineer/Senior Data Engineer to join our Singapore team. The role focuses on building robust data pipelines and scalable architectures to support BI and analytics initiatives.

You will design, implement and maintain data flows, ensure reliability, and collaborate with cross-functional teams in a fast-paced environment. The ideal candidate has 5+ years of experience with Python, Spark and AWS, and will work on Databricks-based pipelines,

Qualifications

• Proficient in Python, PySpark and SQL with distributed processing, complex transformations, and testing.
• Hands-on experience with Databricks, Apache Spark and Delta Lake for production-scale batch or streaming data engineering.
• Hands-on AWS data engineering experience with S3, Glue, Redshift, IAM, and CloudWatch.
• Experience designing lakehouse or data-lake architectures with layered data patterns and dimensional modeling.
• Experience implementing incremental ingestion, CDC, idempotency, late-arriving data handling, backfills and replay.
• Experience with data quality, schema validation, reconciliation, metadata and lineage as automated parts of pipelines.
• Experience with workflow orchestration, CI/CD, IaC such as Terraform, and environment promotion controls.
• Ability to implement pipeline observability, dashboards, alerting and incident response.
• Knowledge of cloud security basics, least-privilege access, encryption and audit logging.
• Ability to review designs and coach junior engineers.

Skills

Python

PySpark

SQL

Databricks

Apache Spark

Delta Lake

AWS data engineering

Data lakehouse architecture

CDC / Change data capture

Data quality / metadata governance

CI/CD / Terraform / IaC

Pipeline observability

Job description

We're Hiring: Data Engineer/Senior Data Engineer!

We are looking for a skilled and driven Data Engineer/Senior Data Engineer to join our team in Singapore. The ideal candidate will have at least 5 years of experience designing, building, and maintaining robust data pipelines and architectures. You will play a key role in ensuring the reliability, scalability, and performance of our data infrastructure to support business intelligence and analytics initiatives.

Location: Singapore, Singapore

Work Mode: Work from Office

Role: Data Engineer/Senior Data Engineer

What You'll Do:B.

Technical & Professional CompetenciesEssential (Must-Have)

• Strong Python, PySpark and SQL capability, including distributed processing, complex transformations, queryoptimisation, debugging and automated testing.
• Hands-on experience with Databricks, Apache Spark and Delta Lake for production-scale batch or streamingdata engineering.
• Hands-on AWS data engineering experience with a relevant mix of S3, Glue, Lake Formation, IAM, KMS, Lambda,Step Functions, Event Bridge, CloudWatch, Redshift and MSK/Kinesis.
• Experience designing lakehouse or data-lake architectures, including layered data patterns, dimensional ordomain data modelling and reusable curated datasets.
• Experience implementing incremental ingestion, change data capture, idempotency, late-arriving data handling,backfills, replay and recovery.
• Experience implementing data quality, schema validation, reconciliation, metadata and lineage as automatedparts of production pipelines.
• Experience with workflow orchestration, Git-based development, CI/CD, infrastructure as code such asTerraform, and environment promotion controls.
• Ability to implement pipeline observability, operational dashboards, alerting, runbooks, incident diagnosis andservice recovery.
• Working knowledge of cloud security, least-privilege access, network boundaries, encryption, secretmanagement, data classification and audit logging.
• Ability to review technical designs and code, establish engineering standards, and guide less-experiencedengineers.

Eager to shape the future of data?