Senior Data Engineer – Databricks (Financial Services Sector)
Job Title:
Senior Data Engineer – Databricks (Financial Services Sector) Location:
Tanjong Pagar, Singapore Salary:
Up to SGD$10,500+ per month Job Type:
Contract (12 months renewable)
About the Opportunity: We are recruiting for a
Senior Data Engineer
to join a prestigious
Global Financial Institution
based in Tanjong Pagar. This is a high-impact role where you will help build and optimize next-generation data infrastructure for one of the world's leading investment firms.
Why This Role High-Profile Project:
Work on critical data engineering initiatives for a top-tier financial client. Cutting-Edge Tech:
Deep dive into
Databricks ,
PySpark , and modern Lakehouse architectures. Competitive Package:
Salary up to
$10,500+
per month, plus comprehensive benefits. Prime Location:
Based in the heart of Singapore (Tanjong Pagar).
Key Responsibilities: Design, build, and maintain scalable, production-grade ETL/ELT pipelines using
PySpark
and
Databricks . Implement robust data models (Dimensional, Data Vault, or Lakehouse) to ensure scalability and performance. Optimize Spark jobs, manage cluster configurations, and orchestrate workflows within the Databricks environment. Leverage
Delta Lake
features such as ACID transactions, schema evolution, and time travel. Refactor legacy code into modern frameworks and best practices. Collaborate with cross-functional teams to ensure data governance, security, and quality standards are met. Utilize
Workspace AI Agent
capabilities for automation and intelligent workflow improvements.
Required Qualifications: Experience:
Minimum 5
years
of experience in Data Engineering or related roles. Databricks:
At least
2–3 years
of hands-on experience with the Databricks platform (Workspace, Clusters, Notebooks, Job Orchestration). Technical Skills: Strong proficiency in
PySpark
(DataFrames API, Spark SQL, performance tuning). Strong
Python
programming skills for data processing and automation. Proficiency in
SQL
for complex queries and transformations. Architecture:
Experience with Cloud Platforms (Azure, AWS, or GCP) and Data Modeling techniques. Soft Skills:
Excellent problem-solving abilities, strong communication skills, and experience working in Agile environments.
Certifications: Preferred:
Databricks Certified Data Engineer Associate or Professional. Note:
Certification is not mandatory to apply.
We prioritize technical skill and experience over credentials. If you pass the interview, you are welcome to obtain the certification
after
joining the team. We support your professional growth.
Senior Data Engineer – Databricks (Financial Services Sector) Location:
Tanjong Pagar, Singapore Salary:
Up to SGD$10,500+ per month Job Type:
Contract (12 months renewable)
About the Opportunity: We are recruiting for a
Senior Data Engineer
to join a prestigious
Global Financial Institution
based in Tanjong Pagar. This is a high-impact role where you will help build and optimize next-generation data infrastructure for one of the world's leading investment firms.
Why This Role High-Profile Project:
Work on critical data engineering initiatives for a top-tier financial client. Cutting-Edge Tech:
Deep dive into
Databricks ,
PySpark , and modern Lakehouse architectures. Competitive Package:
Salary up to
$10,500+
per month, plus comprehensive benefits. Prime Location:
Based in the heart of Singapore (Tanjong Pagar).
Key Responsibilities: Design, build, and maintain scalable, production-grade ETL/ELT pipelines using
PySpark
and
Databricks . Implement robust data models (Dimensional, Data Vault, or Lakehouse) to ensure scalability and performance. Optimize Spark jobs, manage cluster configurations, and orchestrate workflows within the Databricks environment. Leverage
Delta Lake
features such as ACID transactions, schema evolution, and time travel. Refactor legacy code into modern frameworks and best practices. Collaborate with cross-functional teams to ensure data governance, security, and quality standards are met. Utilize
Workspace AI Agent
capabilities for automation and intelligent workflow improvements.
Required Qualifications: Experience:
Minimum 5
years
of experience in Data Engineering or related roles. Databricks:
At least
2–3 years
of hands-on experience with the Databricks platform (Workspace, Clusters, Notebooks, Job Orchestration). Technical Skills: Strong proficiency in
PySpark
(DataFrames API, Spark SQL, performance tuning). Strong
Python
programming skills for data processing and automation. Proficiency in
SQL
for complex queries and transformations. Architecture:
Experience with Cloud Platforms (Azure, AWS, or GCP) and Data Modeling techniques. Soft Skills:
Excellent problem-solving abilities, strong communication skills, and experience working in Agile environments.
Certifications: Preferred:
Databricks Certified Data Engineer Associate or Professional. Note:
Certification is not mandatory to apply.
We prioritize technical skill and experience over credentials. If you pass the interview, you are welcome to obtain the certification
after
joining the team. We support your professional growth.