Databricks Data Engineer

re-zoo-me; Singapore; Hybrid; SGD 120,000 - 170,000; Full time

Job summary

re-zoo-me seeks a hands-on data engineer with deep Databricks expertise to design and operationalize Delta Lakehouse architectures for enterprise customers. You will own implementations, lead technical delivery, and mentor teams on data governance, AI, and best practices.

You will build scalable pipelines with DLT, Spark SQL, Python/Scala, manage Workspaces and Unity Catalog, automate deployments with Terraform, and drive observability and cost optimization across AWS/Azure/GCP environments.

Qualifications

• 6–10 years hands-on Databricks experience including workspace setup, notebooks, clusters and orchestration.
• Expertise in Delta Lake, DLT, Unity Catalog, and SQL Warehouses.
• Proficiency in Python or Scala for data engineering and ML workflows.
• Strong understanding of AWS, Azure, or GCP cloud ecosystems.
• Experience with Terraform automation, DevOps, and MLOps practices.

Responsibilities

• Design and implement scalable data pipelines using Delta Live Tables, Spark SQL, Python, or Scala.
• Optimize ETL, streaming, and ML workloads for performance, cost, and reliability.
• Administer and configure Databricks Workspaces, Unity Catalog, and cluster policies for secure environments.
• Automate infrastructure and deployments using Terraform, Git, and CI/CD pipelines.
• Implement observability and cost optimization with Splunk, Prometheus, or CloudWatch.
• Collaborate with customers to build AI and LLM solutions leveraging MLflow, DBRX, and Mosaic AI.

Skills

Databricks

Delta Live Tables

Spark SQL

Python

Scala

SQL Warehouses

DevOps

MLOps

Tools

Terraform

MLflow

Unity Catalog

DBRX

Mosaic AI

Git

CI/CD tools

Splunk

Prometheus

CloudWatch

Job description

We’re seeking a hands-on experience in Databricks with deep technical expertise in building and optimizing Lakehouse-based data and AI solutions.

In this role, you’ll design, develop, and operationalize Delta Lakehouse architectures using Databricks, driving real-world outcomes for enterprise customers. You’ll take ownership of implementation tasks, lead technical delivery, and mentor engineering teams in best practices across data engineering, governance, and AI.

Key Responsibilities

• Design and implement scalable data pipelines using Delta Live Tables (DLT), Spark SQL, Python, or Scala.
• Optimize ETL, streaming, and ML workloads for performance, cost efficiency, and reliability.
• Administer and configure Databricks Workspaces, Unity Catalog, and cluster policies for secure, governed environments.
• Automate infrastructure and deployments using Terraform, Git, and CI/CD pipelines.
• Implement observability, cost optimization, and monitoring frameworks using tools like Splunk, Prometheus, or CloudWatch.
• Collaborate with customers to build AI and LLM solutions leveraging MLflow, DBRX, and Mosaic AI.

Required Skills & Experience

• 6 to10 Years for Strong hands-on experience with Databricks, including workspace setup, notebooks, clusters, and job orchestration.
• Expertise in Delta Lake, DLT, Unity Catalog, and SQL Warehouses.
• Proficiency in Python or Scala for data engineering and ML workflows.
• Strong understanding of AWS, Azure, or GCP cloud ecosystems.
• Experience with Terraform automation, DevOps, and MLOps practices.

Familiarity with monitoring and governanceframeworks for large-scale data platforms.