Data Engineer, Digital Transformation & Data (DT&D)

BOC Aviation; Singapore; On-site; SGD 150,000 - 190,000; Full time

Job summary

BOC Aviation is seeking a Senior Data Engineer to design, develop and optimize data pipelines across diverse sources in a cloud environment. You will implement data quality checks, govern data and algorithms, and manage complex data models.

The role requires 10+ years in data management with strong Python/PySpark, SQL, and Azure Databricks experience, along with proficiency in CI/CD practices and BI tools.

Qualifications

• Bachelor’s degree or higher in a quantitative field.
• Ten years in data management disciplines or related areas.

Responsibilities

• Design and develop new data pipelines and manage existing ones from various sources.
• Implement data quality checks to ensure data accuracy, consistency and completeness.
• Transform data with cleansing, aggregation, filtering and enrichment techniques.
• Establish governance of data and algorithms used for analysis and ML deployment.
• Manage logical and physical data models.
• Ensure compliance with security and governance best practices.
• Implement and maintain CI/CD pipelines and cloud provisioning.
• Optimize data pipelines for performance and scalability.
• Support deployment of AI solutions within the data platform.
• Guide business users to create and maintain reports and dashboards.

Skills

Python/PySpark

SQL

Azure

Databricks

CI/CD (Azure DevOps)

Data governance

Power BI

Big data pipelines

NoSQL

Education

Bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field

Master’s degree preferred

Tools

Azure cloud services

Databricks LakeFlow

Unity Catalog

Microsoft Purview

Power BI

Job description

Reporting to Data and Analytics Lead, the successful candidate will be responsible for the following:

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.
• 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 ten 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 four 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.
• Align with and demonstrate BOC Aviation Core Values, which are Integrity; Teamwork; Accountability; Agility; and Ambition.