Data Engineer

Recruit Express Pte Ltd; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

Recruit Express Pte Ltd seeks a Data Management & Transformation professional to design and develop data pipelines, ensuring quality and governance across enterprise systems.

You will transform data with cleansing, aggregation, and enrichment while maintaining data models and collaborating with business users to derive insights, all within a secure governance framework.

Qualifications

• Bachelor's degree in CS/DS/SE/IS; advanced degree preferred.
• 6+ years in data management, integration, modelling, quality.
• 4+ years designing data architectures in Azure and Databricks.
• Strong Python (PySpark) and SQL; Java/Scala a plus.
• Experience with SQL/NoSQL databases; Oracle preferred.
• Experience with Azure DevOps and CI/CD pipelines.
• Familiarity with Unity Catalog and Purview.
• BI & visualization with Power BI.

Responsibilities

• Design and develop new data pipelines and manage existing ones.
• Implement data quality checks and validations.
• Transform data via cleansing, aggregation, filtering, and enrichment.
• Establish governance of data and algorithms for analysis.
• Collaborate with data lead and business users to manage data as a business asset.
• Monitor and optimize pipelines for performance and scalability.

Skills

Python (PySpark)

SQL

Java/Scala

Education

Bachelor's degree in computer science / data science / software engineering / information systems or related quantitative field

Master's degree preferred

Tools

Azure DevOps

Databricks

Unity Catalog

Microsoft Purview

Power BI

Job description

Data Management & Transformation

Designing and developing new data pipelines and managing existing data pipelines that extract data from various business applications, databases, and external systems.

Implementing data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data.

Transforming data into the desired format by applying data cleansing, aggregation, filtering, and enrichment techniques.

Establishing the governance of data and algorithms used for analysis, analytical applications, and automated decision-making.

Manage the logical and physical data models to capture the structure, relationships, and constraints of relevant datasets.

Ensuring compliance with security and governance best practices.

Optimization & Automation

Implementing and maintaining continuous integrations and continuous delivery pipelines for deployments and cloud resource provisioning.

Optimising data pipelines and data processing workflows for performance, scalability, and efficiency.

Optimising models and algorithms for data quality, security, governance, performance and scalability needs.

Routinely assessing processor and storage capacity across the data warehouse and extract transform & load platforms, including capacity planning and forecasting.

Monitoring and tuning data system, identifying and resolving performance bottlenecks, issues, and implementing caching and indexing strategies to enhance query performance.

Monitoring the platform for credit consumption and housekeeping.

Supporting the deployment and maintenance of AI solutions in the data platform.

Collaboration

Working with data lead and business users to manage data as a business asset.

Guiding the business users to create and maintain reports and dashboards.

Job Requirements

Bachelor's degree in computer science, data science, software engineering, information systems, or related quantitative field; Master's degree preferred.

At least 6 years of work experience in data management disciplines, including data integration, modelling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks.

At least 4 years of work experience in designing and implementing data architectures in Azure cloud services and Databricks.

Strong proficiency in Python (PySpark) and SQL programming; experience with Java or Scala is an advantage.

Experience with relational and non-relational databases including SQL and NoSQL is a must while familiarity with legacy databases such as Oracle is preferred.

Experience using Azure DevOps, Databricks LakeFlow Jobs for DevOps practices including version control, CI/CD and pipeline deployment.

Experience with data catalogue tools including Unity Catalog and Microsoft Purview.

Familiarity with BI & visualisation tools such as Power BI and Python visual packages for data analytics is preferred.

Experience supporting AI/ML model deployment, feature engineering and production inference is preferred.

We regret that only shortlisted candidates will be contacted.