Data Platform Architect

Tap Growth ai; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Tap Growth ai is hiring an experienced Data Platform Architect to lead the design, development, and optimization of enterprise-scale data platforms and modern analytics ecosystems. The role focuses on cloud-native solutions, scalable pipelines, and AI-enabled analytics across governance and security.

The ideal candidate has 8+ years in data engineering or architecture, with strong Snowflake, Spark, Airflow, Kafka, and Iceberg expertise, and a track record of guiding large data initiatives.

Qualifications

• Bachelor's degree in a related field required.
• 8+ years of experience in Data Engineering, Data Platforms, Big Data, Analytics, or Data Architecture.
• 6+ years hands-on experience delivering enterprise data solutions.

Responsibilities

• Design and architect scalable, cloud-native data platforms and analytics solutions.
• Lead the development of enterprise data pipelines, ingestion frameworks, and lakehouse architectures.
• Define data architecture standards, best practices, and technology roadmaps.
• Design and optimize ETL/ELT frameworks supporting large-scale data processing workloads.
• Collaborate with business stakeholders, architects, data scientists, and engineering teams to deliver data-driven solutions.
• Drive data platform modernization, automation, and cloud migration initiatives.
• Architect and support distributed data processing environments using Spark-based technologies.
• Establish governance, performance, scalability, security, and operational standards across the data ecosystem.
• Provide technical leadership, mentoring, and architectural oversight to data engineering teams.
• Evaluate and recommend emerging technologies to support enterprise data and AI initiatives.

Skills

Snowflake

Spark / PySpark

ETL / ELT frameworks

Kafka

Airflow

Iceberg

Cloud data platforms

AI/ML workloads integration

Data modeling

Distributed processing

Education

Bachelor's Degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or related discipline

Tools

Snowflake

Apache Spark / PySpark

Apache Airflow

Apache Kafka

Apache Iceberg

Databricks

GBI ETL Frameworks

Job description

We're Hiring: Data Platform Architect!

We are seeking a highly experienced Data Platform Architect to lead the design, development, and optimization of enterprise-scale data platforms and modern analytics ecosystems. This role will be responsible for architecting cloud-native data solutions, designing scalable data pipelines, enabling AI-driven analytics, and establishing best practices across data engineering, integration, and platform governance.

The ideal candidate possesses strong expertise in cloud data platforms, big data technologies, lakehouse architectures, and modern ETL frameworks, with the ability to provide technical leadership and architectural guidance across complex data initiatives.

Key Responsibilities

• Design and architect scalable, cloud-native data platforms and modern analytics solutions.

• Lead the development of enterprise data pipelines, ingestion frameworks, and lakehouse architectures.

• Define data architecture standards, best practices, and technology roadmaps.

• Design and optimize ETL/ELT frameworks supporting large-scale data processing workloads.

• Collaborate with business stakeholders, architects, data scientists, and engineering teams to deliver data-driven solutions.

• Drive data platform modernization, automation, and cloud migration initiatives.

• Architect and support distributed data processing environments using Spark-based technologies.

• Establish governance, performance, scalability, security, and operational standards across the data ecosystem.

• Provide technical leadership, mentoring, and architectural oversight to data engineering teams.

• Evaluate and recommend emerging technologies to support enterprise data and AI initiatives.

General Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related discipline.

• 8+ years of overall experience in Data Engineering, Data Platforms, Big Data, Analytics, or Data Architecture.

• 6+ years of hands‑on experience designing and delivering enterprise data solutions.

Mandatory Skills

• Strong experience with Snowflake and cloud-based data platforms.

• Hands‑on expertise in Spark, Apache Spark, and PySpark.

• Experience designing and supporting modern ETL/ELT frameworks.

• Knowledge of GBI ETL Frameworks and enterprise data integration practices.

• Strong experience with Apache Airflow for workflow orchestration and automation.

• Experience with Apache Kafka and event-driven data architectures.

• Hands‑on experience with Apache Iceberg and modern lakehouse architectures.

• Strong understanding of Cloud Computing platforms and cloud-native data solutions.

• Experience integrating Artificial Intelligence / Machine Learning workloads with enterprise data platforms.

• Expertise in data modeling, data warehousing, analytics platforms, and distributed processing frameworks.

Nice-to-Have Skills

• Data mesh or domain-driven data architecture experience.

• Databricks platform experience.

• Cloud certifications (AWS, Azure, or GCP).

• Real-time streaming and event-driven architectures.

• Infrastructure-as-Code and DevOps practices.

• Experience supporting AI/ML, predictive analytics, and Generative AI initiatives.

• Experience within Financial Services, Manufacturing, Supply Chain, Retail, or large enterprise environments.