Lead/Senior Data Engineer

Zenith Infotech Pte Ltd.

Singapore

On-site

SGD 120,000 - 180,000

Full time

8 days ago
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Job summary

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.

Qualifications

  • 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.

Responsibilities

  • 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.

Skills

SQL
Python/Scala
Spark
Databricks
Airflow

Education

Degree in Computer Science, IT, Data Engineering or related

Tools

Databricks Lakehouse
Delta Lake
Airflow

Job description

Role
  • 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.
Requirements
  • Degree in Computer Science, IT, Data Engineering or related.
  • 5+ years in data engineering with experience leading projects or small teams.
  • Strong in SQL, Python /Scala, and Spark on Databricks.
  • Hands-on with Databricks Lakehouse platform, Delta Lake, ETL/ELT frameworks and orchestration (e.g., Airflow / Databricks Workflows).
  • Proven experience building and operating Data Lakes and Data Warehouses at scale.
  • Experience with relational databases, cloud platforms, and building secure, production-grade data pipelines.
  • Strong ownership, problem-solving and communication skills.
  • This role will need to secure a clearance, due to the sensitivity of the project.

EA Licence No: 20S0237

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