Data Engineer (AWS, Central Location)

re-zoo-me; Singapore; Hybrid; SGD 120,000 - 180,000; Full time

Job summary

re-zoo-me is seeking a Senior Data Engineer to design, build and operate enterprise-grade data platforms that support analytics, data science and digital products. You will contribute to data architecture, engineering standards and technical decision-making in a complex enterprise environment.

The role emphasizes scalable data pipelines, robust data models, and collaboration with engineers, product managers and analysts to deliver high-quality data solutions.

Qualifications

• 7+ years in software/data engineering with strong Python and SQL.
• Experience with AWS and modern data platforms (Redshift, Snowflake, Databricks, BigQuery).
• Expertise in data architectures, pipelines, data warehouses/lakes.
• Knowledge of data orchestration, transformation, and modelling.

Responsibilities

• Design, build and maintain scalable data architectures and pipelines for ingestion, transformation and delivery.
• Develop robust data models and reusable data capabilities for analysts and data scientists.
• Improve reliability, security, performance, observability of data platforms.
• Evaluate technologies and make sound architectural trade-offs.
• Champion CI/CD, automated testing, and IaC practices.
• Collaborate with engineers, PMs, data scientists and analysts, providing technical leadership.

Skills

Python

SQL

AWS

Data modeling

CI/CD

Data quality

Tools

Redshift

Snowflake

Databricks

BigQuery

Airflow

dbt

Job description

Our client is looking for a Senior Data Engineer to design, build and operate enterprise-grade data platforms supporting analytics, data science and digital products. The role will contribute to data architecture, engineering standards and technical decision-making in a complex enterprise environment.

Responsibilities

• Design, build and maintain scalable data architectures and pipelines for data ingestion, transformation and delivery.
• Develop robust data models and reusable data capabilities for analysts, data scientists and applications.
• Improve the reliability, security, performance, observability and maintainability of data platforms.
• Evaluate technologies and architectural approaches, making sound technical trade-offs and contributing to engineering standards.
• Champion modern engineering practices including automated testing, code reviews, CI/CD and Infrastructure-as-Code.
• Collaborate with engineers, Product Managers, Data Scientists and analysts, while providing technical leadership, mentoring and knowledge sharing.

Requirements

• 7+ years of experience in software/data engineering with strong Python and SQL skills.
• Experience with AWS and modern data platforms such as Redshift, Snowflake, Databricks or BigQuery.
• Strong experience in enterprise data architecture and engineering, including production data systems.
• Hands-on experience designing data pipelines, data models, data warehouses, data lakes or lakehouse architectures.
• Experience with data orchestration, transformation and modelling.
• Strong understanding of production engineering practices including testing, CI/CD, monitoring, troubleshooting and data quality.

Good to Have

• Experience with Apache Airflow, dbt and/or Apache Spark.
• Strong knowledge of AWS data services and cloud infrastructure.
• Experience with Tableau, Power BI or similar BI tools.
• Knowledge of Infrastructure-as-Code, data observability, metadata, data catalogues or data lineage.
• Experience working with sensitive or regulated data.