Lead Data Lakehouse Architect (Databricks)

Zenith Infotech Pte Ltd.; Singapore; Presencial; SGD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Zenith Infotech Pte Ltd. in Singapore seeks a senior data engineer lead to architect and deliver Data Lake, Data Warehouse, and Lakehouse solutions on Databricks, while shaping scalable ETL pipelines and data infrastructure.

You will lead a team, implement data security and governance, optimize Spark workloads, and collaborate with analysts and data scientists to produce trusted data products for diverse business units.

Formación

• Degree in Computer Science, IT, Data Engineering or related field.
• 5+ years in data engineering with leadership experience.
• Strong in SQL, Python/Scala, and Spark on Databricks.

Responsabilidades

• Lead the architecture, design and delivery of Data Lake, Data Warehouse and Lakehouse platforms, including on Databricks.
• Own and build scalable, reliable ETL/ELT pipelines and large-scale ingestion from diverse structured and unstructured sources.
• Build and manage data infrastructure on Databricks and modern data stack (Spark, Delta Lake).
• Define and drive data modeling (dimensional, Data Vault), data quality, and data governance standards across Lake and Warehouse layers.
• Optimize data processing jobs and SQL / Spark workloads for performance, reliability and cost on Databricks.
• Implement data security, access control, data lineage and compliance practices.
• Provide technical leadership, mentorship and code reviews to the team.
• Partner with analysts, data scientists and application teams to deliver trusted data products.

Conocimientos

SQL

Python/Scala

Spark

Databricks

Airflow

Educación

Degree in Computer Science, IT, Data Engineering or related

Herramientas

Databricks Lakehouse

Delta Lake

Airflow

Descripción del empleo

Zenith Infotech Pte Ltd. in Singapore seeks a senior data engineer lead to architect and deliver Data Lake, Data Warehouse, and Lakehouse solutions on Databricks, while shaping scalable ETL pipelines and data infrastructure.

You will lead a team, implement data security and governance, optimize Spark workloads, and collaborate with analysts and data scientists to produce trusted data products for diverse business units.