Data Engineer

ZENITH INFOTECH (S) PTE LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ZENITH INFOTECH (S) PTE LTD. in Singapore seeks an experienced data engineering leader to own the design, development, and scaling of our data platform and pipelines.

You will build scalable ETL/ELT processes with Python and SQL, mentor engineers, drive best practices, partner with Data Science and Analytics, and ensure data security and quality across cloud environments. This role requires hands-on coding, architecture work, end-to-end delivery, and the ability to secure a clearance for

Qualifications

• Masters or Degree in Computer Science, Engineering, Mathematics, or related field.
• Equivalent practical experience will be considered.
• Has at least 6+ years in data engineering, with 2+ years in a lead/senior role.
• Strong in Python and SQL. Experience with PySpark is a plus.
• Hands-on experience with AWS, GCP, or Azure. Services like S3/ADLS, BigQuery/Redshift/Snowflake, Airflow, Kafka, DBT.
• ETL/ELT Tools: Informatica PowerCenter / Informatica Intelligent Cloud Services (IICS).
• Experience with data integration, mappings, transformations, and workflow orchestration in Informatica.
• Strong experience with dimensional modeling, data warehousing, and lakehouse architectures.
• Experience with Airflow, Prefect, or similar workflow tools.
• Engineering practices: CI/CD, Docker, Git, Infrastructure as Code, unit testing.
• Good to Have: Kafka, Spark Streaming, Flink; Databases: PostgreSQL, MongoDB, Redis.
• Working with feature stores and model deployment pipelines.
• Experience hiring, mentoring, and doing technical interviews.
• Can explain complex technical concepts to non-technical stakeholders.
• Proactive problem solver who takes end-to-end ownership.
• Works well across Data Science, Analytics, and Engineering teams.
• The role will need to secure a clearance, due to the sensitivity of the project.

Responsibilities

• Design and implement scalable, reliable, and cost-effective data pipelines and data platforms.
• Build and maintain ETL/ELT pipelines, data models, and APIs using Python, SQL, and modern cloud tools.
• Own data ingestion, storage, transformation, orchestration, and monitoring in cloud environments.
• Guide engineers, conduct code reviews, and drive best practices in data engineering.
• Partner with Data Science, Analytics, Product, and Business teams to translate requirements into technical solutions.
• Drive end-to-end delivery of data projects from requirements gathering to production deployment and support.
• Implement testing, monitoring, and data quality frameworks.
• Enforce data security, privacy, and compliance standards.
• Optimize pipeline performance, cost, and reliability.
• Troubleshoot production issues.

Skills

Python

SQL

Pyspark

ETL/ELT design

Data warehousing

Cloud platforms

CI/CD

Docker

Leadership

Code reviews

Stakeholder communication

Education

Master's degree in CS or related

Equivalent practical experience

Tools

S3/ADLS

BigQuery

Redshift

Snowflake

Airflow

Kafka

DBT

Informatica PowerCenter

Informatica IICS

PowerCenter

Docker

Git

IaC

Job description

Job

• Own the design, development, and scaling of our data platform and pipelines.
• Lead a small team of data engineers, work closely with Data Science, Analytics, and Product, and ensure our data is reliable, scalable, and accessible for decision-making and ML products.
• Be hands-on with architecture and coding, while also mentoring engineers and setting engineering standards.

Role

• Design and implement scalable, reliable, and cost-effective data pipelines and data platforms.
• Build and maintain ETL/ELT pipelines, data models, and APIs using Python, SQL, and modern cloud tools.
• Own data ingestion, storage, transformation, orchestration, and monitoring in cloud environments.
• Guide engineers, conduct code reviews, and drive best practices in data engineering.
• Partner with Data Science, Analytics, Product, and Business teams to translate requirements into technical solutions.
• Drive end-to-end delivery of data projects from requirements gathering to production deployment and support.
• Implement testing, monitoring, and data quality frameworks.
• Enforce data security, privacy, and compliance standards.
• Optimize pipeline performance, cost, and reliability.
• Troubleshoot production issues.

Requirements

• Masters or Degree in Computer Science, Engineering, Mathematics, or related field.
• Equivalent practical experience will be considered.
• Has at least 6+ years in data engineering, with 2+ years in a lead/senior role.
• Strong in Python and SQL. Experience with PySpark is a plus.
• Hands-on experience with AWS, GCP, or Azure. Services like S3/ADLS, BigQuery/Redshift/Snowflake, Airflow, Kafka, DBT.
• ETL/ELT Tools: Informatica PowerCenter / Informatica Intelligent Cloud Services (IICS).
• Experience with data integration, mappings, transformations, and workflow orchestration in Informatica.
• Strong experience with dimensional modeling, data warehousing, and lakehouse architectures.
• Experience with Airflow, Prefect, or similar workflow tools.
• Engineering practices: CI/CD, Docker, Git, Infrastructure as Code, unit testing.
• Good to Have: Kafka, Spark Streaming, Flink; Databases: PostgreSQL, MongoDB, Redis.
• Working with feature stores and model deployment pipelines.
• Experience hiring, mentoring, and doing technical interviews.
• Can explain complex technical concepts to non-technical stakeholders.
• Proactive problem solver who takes end-to-end ownership.
• Works well across Data Science, Analytics, and Engineering teams.
• The role will need to secure a clearance, due to the sensitivity of the project.