Databricks Data Engineer

UARROW PTE. LTD.; Singapore; Hybrid; SGD 80,000 - 120,000; Full time

Job summary

A technology consulting firm is seeking a hands-on Senior Consultant – Databricks in Singapore. This contract role involves designing and operationalizing Delta Lakehouse architectures, leading implementation tasks, and mentoring engineering teams. Ideal candidates will have strong experience with Databricks, Python or Scala, and cloud ecosystems such as AWS or Azure. The position offers flexibility to work on-site or remotely within the region, driving real-world AI and data solutions for enterprise customers.

Qualifications

• Experience in building and optimizing Lakehouse-based data solutions.
• Strong hands-on experience with Databricks including workspace setup and orchestration.
• Familiarity with monitoring and governance frameworks for large-scale platforms.

Responsibilities

• Design and implement scalable data pipelines using Delta Live Tables, Spark SQL, Python, or Scala.
• Optimize ETL, streaming, and ML workloads for efficiency and reliability.
• Collaborate with customers to build AI and LLM solutions leveraging Databricks.

Skills

Databricks

Python

Scala

Delta Lake

AWS

Azure

GCP

Terraform

DevOps

MLOps

Tools

Git

CloudWatch

Splunk

Prometheus

Job description

•We’re seeking a hands-on Senior Consultant – Databricks with deep technical expertise in building and optimizing Lakehouse-based data and AI solutions. This is a contract role based in Singapore, offering flexibility to work on-site with clients or remotely within the region.

•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

• 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 governance frameworks for large-scale data platforms.

Nice to Have

• Experience developing AI/LLM pipelines and RAG architectures on Databricks.
• Exposure to Bedrock, OpenAI, or Hugging Face integrations.
• Databricks certifications (Data Engineer, Machine Learning, or Solutions Architect) preferred.