Summary
Data Engineer in Singapore designing, building, and optimizing data pipelines on Azure and Databricks, covering ETL, data quality, governance, CI/CD deployment, and performance tuning, plus supporting AI/ML solutions. Requires 6+ years in data engineering, 4+ years with Azure/Databricks, and strong Python (PySpark) and SQL skills.
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.
Interested applicants please send your resume to (HIDDEN TEXT)
Venessa Goh Wee Ni
R24124686
Recruit Express Pte Ltd
EA License No: 99C4599
We regret that only shortlisted candidates will be contacted.