Senior Data Engineer

Tap Growth ai; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

Tap Growth ai in Singapore is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and data infrastructure to support analytics and decision-making.

You will collaborate with engineers, product managers, data scientists, and analysts, applying best practices in data modeling, testing, CI/CD, and observability while working in an office-based environment.

Qualifications

• Proficient in Python and SQL with strong data modeling skills.
• Experience building and operating production-grade data systems.
• Expertise in enterprise data architecture and engineering.

Responsibilities

• Design data pipelines, architectures, models and reusable data capabilities.
• Apply engineering practices to improve reliability, security, observability and performance.
• Evaluate technologies and contribute to data architecture and engineering standards.
• Promote automated testing, code review, CI/CD and infrastructure-as-code.
• Collaborate with engineers, PMs, data scientists and analysts.
• Provide technical leadership through design reviews and mentoring.

Skills

Python

SQL

Data pipelines

Data warehouses

AWS

Redshift

Snowflake

Databricks

Data lakes

Lakehouse

Airflow

Spark

Tableau

Power BI

Tools

Apache Airflow

Apache Spark

Tableau

Power BI

Job description

We're Hiring: Senior Data Engineer!

We are looking for a talented and detail-oriented Senior Data Engineer to join our dynamic team in Singapore. In this role, you will design, build, and maintain scalable data pipelines and infrastructure to support business analytics and decision-making. If you have a passion for data engineering and thrive in a collaborative environment, we want to hear from you!

Location: Singapore, Singapore
Work Mode: Work from Office
Role: Senior Data Engineer

Key Responsibilities

• Design data pipelines, architectures, models and reusable data capabilities.
• Apply engineering practices to improve reliability, security, observability and performance.
• Evaluate technologies and contribute to data architecture and engineering standards.
• Promote automated testing, code review, CI/CD and infrastructure-as-code.
• Work with engineers, Product Managers, Data Scientists, analysts and users.
• Provide technical leadership through design reviews, mentoring and knowledge sharing.

Requirements

• Strong software engineering skills with Python and SQL.
• Experience building and operating complex production data systems.
• Strong enterprise data architecture and engineering experience.
• Experience with data pipelines, data modelling, data warehouses, data lakes and lakehouse architectures.
• Experience with AWS and modern data platforms such as Redshift, Snowflake, Databricks or BigQuery.
• Experience with data orchestration, transformation and modelling.
• Strong understanding of testing, CI/CD, monitoring, troubleshooting and data quality.

Good to Have

• Apache Airflow or equivalent.
• Apache Spark.
• AWS data services and cloud infrastructure.
• Tableau, Power BI or equivalent.
• Infrastructure-as-code, data observability, metadata, catalogue or lineage.
• Experience with sensitive or regulated data and technology/data for public good.