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Open nowPosted yesterday

Databricks Engineer

MyCareersFuture91,045 open roles

Pay
SGD 5,000 – SGD 6,000 a month
Where
Central, Singapore
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Your applicationOpen nowDatabricks EngineerMyCareersFuture · Central, Singapore

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 1 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted yesterday

MyCareersFuture median: 1 days open

The posting

About the Role

We are looking for a skilled Databricks Engineer todesign, develop, and maintain scalable data engineering solutions using the DatabricksLakehouse Platform.

The ideal candidate will have strong hands-on experiencewith Databricks, Apache Spark, Python, SQL, Delta Lake, and cloud dataplatforms, with the ability to build reliable and high-performance datapipelines.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.
  • Develop ETL/ELT pipelines using PySpark, Python, and SQL.
  • Build and maintain Delta Lake tables and data processing workflows.
  • Work with Databricks Lakehouse architecture and related data engineering components.
  • Develop batch and, where required, near-real-time data processing solutions.
  • Ingest and transform data from databases, APIs, files, and other data sources.
  • Implement data cleansing, transformation, validation, and quality checks.
  • Optimise Spark jobs and Databricks workloads for performance and cost efficiency.
  • Work with cloud storage and data services across Azure, AWS, or GCP.
  • Implement data security, access controls, and governance within the data platform.
  • Collaborate with Data Architects, Data Scientists, BI Developers, and business stakeholders.
  • Troubleshoot data pipeline failures and resolve performance and data-quality issues.
  • Develop and maintain technical documentation for data pipelines and solutions.
  • Participate in code reviews, testing, deployment, and production support.
  • Follow Agile development practices and contribute to continuous improvement.

Required Skills & Experience

  • 3–5 years of experience in Data Engineering.
  • Strong hands-on experience with Databricks.
  • Strong knowledge of:
  • Apache Spark / PySpark
  • Python
  • SQL
  • Delta Lake
  • ETL/ELT concepts
  • Experience developing and managing data pipelines.
  • Good understanding of data warehousing and data modelling concepts.
  • Experience working with cloud platforms, preferably Microsoft Azure.
  • Experience with cloud storage such as Azure Data Lake Storage (ADLS), Amazon S3, or Google Cloud Storage.
  • Experience with relational and/or NoSQL databases.
  • Good understanding of data quality, validation, and governance.
  • Familiarity with Git and CI/CD practices.
  • Strong troubleshooting and analytical skills.

Good to Have

  • Databricks Certified Data Engineer Associate/Professional certification.
  • Experience with Azure Data Factory.
  • Experience with Microsoft Fabric.
  • Knowledge of Unity Catalog and Databricks governance.
  • Experience with Databricks Workflows and job orchestration.
  • Experience with streaming technologies such as Kafka or Structured Streaming.
  • Experience with Power BI or other BI platforms.
  • Exposure to Machine Learning workflows on Databricks.
  • Experience with Terraform or Infrastructure as Code.
  • Knowledge of DevOps and CI/CD pipelines.

Candidate Profile

The ideal candidate should be a hands-on Databricks/Data Engineer capable of independently developing data pipelines, troubleshooting production issues, optimising Spark workloads, and collaborating with technical and business teams.

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