Databricks Data Engineer

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

Job summary

A data consultancy firm in Singapore seeks a Senior Consultant – Databricks to design and operationalize Delta Lakehouse architectures. The role involves leading implementation tasks, optimizing data pipelines, and mentoring teams. Strong hands-on experience with Databricks, proficiency in Python or Scala, and knowledge of cloud ecosystems are essential. Candidates will enjoy flexible working arrangements, whether on-site or remote.

Qualifications

• Strong hands-on experience with Databricks including workspace setup.
• Expertise in Delta Lake, DLT, Unity Catalog, and SQL Warehouses.
• Proficient in Python or Scala for data engineering workflows.

Responsibilities

• Design and implement scalable data pipelines using Delta Live Tables.
• Optimize ETL, streaming, and ML workloads for performance and cost efficiency.
• Administer and configure Databricks Workspaces and Unity Catalog.

Skills

Databricks expertise

Python or Scala proficiency

AWS, Azure, or GCP understanding

Terraform automation

Monitoring frameworks familiarity

Tools

Databricks

Terraform

Splunk

Prometheus

CloudWatch

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.