Data & AI Engineer (12 Months)

Zurich 56 Company Ltd; Singapore; On-site; SGD 80,000 - 110,000; Full time

Job summary

A global insurance provider in Singapore is seeking an experienced Data & AI Engineer to enhance and maintain data platform architecture. You will play a crucial role in operationalizing AI solutions and optimizing data architecture. The ideal candidate should have 8+ years of experience in Data Engineering, advanced SQL skills, and knowledge of Azure Cloud services. This is an exciting opportunity to join a dynamic team focused on innovation and data-driven insights.

Benefits

Career growth opportunities

Commitment to employee well-being

Qualifications

• Approximately 8+ years of experience in a Data Engineer role.
• Advanced working knowledge of SQL and experience with relational databases.
• Experience in building and optimizing 'big data' pipelines.
• Proven history of manipulating and processing large datasets.
• Experience in developing and integrating Power BI reports.

Responsibilities

• Delivering solutions using advanced techniques in data modeling and ETL.
• Integration and structuring of large data sets.
• Designing and maintaining data pipelines in Azure Cloud.
• Collaborating with data scientists for GenAI use cases.
• Monitoring and resolving data pipeline issues.

Skills

SQL

Data Engineering

Data Visualization

Databricks

Python

Azure Cloud Services

ETL

Data Modeling

Power BI

Problem Solving

Education

Degree in Computer Science, Data Science, Information Systems or related field

Tools

Azure Data Factory

Control-M

Airflow

Stream-processing systems (e.g., Storm, Spark-Streaming)

Job description

We are seeking a skilled Data & AI Engineer to join our Data & Digital team. This role focuses on enhancing and maintaining data platform architecture, operationalizing Generative AI solutions, and implementing automation solutions.
This individual must be self-directed and comfortable in addressing the data needs of multiple teams, systems, and products. The right candidate will be enthusiastic about the opportunity to optimize or even redesign the data architecture to support the next generation of products and data initiatives.
The expertise of the Data & AI Engineer is crucial in building a robust data & AI infrastructure so that all stakeholders have seamless access to reliable and accurate data.

Your Role

• Delivering solutions using advanced techniques in data modeling, ETL, data visualization, and more to derive insights from both structured and unstructured data.
• Maintaining, reviewing, and supporting the development of automation solutions.
• Integrating, consolidating, cleansing, and structuring large data sets to facilitate business insights and reporting.
• Designing, implementing, and maintaining data pipelines for data ingestion, processing, and transformation in Azure Cloud.
• Proactively understanding business requirements and translating them into superior software implementations using an agile approach.
• Collaborating with data scientists and analysts to understand data needs and operationalize GenAI use cases and automation.
• Set up robust cloud infrastructure to enable reliable and scalable deployment of AI/ML solutions in production. Deploy models as APIs or microservices to integrate seamlessly with existing applications, applying MLOps and DevOps best practices.
• Utilizing Databricks, Azure Data Factory, or similar technologies to create and maintain ETL operations, including data quality checks.
• Enhancing the scalability, efficiency, and cost-effectiveness of data pipelines.
• Monitoring and resolving data pipeline issues to ensure data consistency and availability, while working towards improving data quality.
• Defining and implementing data governance processes.

Your Skills and Experience

• Approximately 8+ years of experience in a Data Engineer role with a degree in Computer Science, Data Science, Information Systems, or a related field.
• Advanced working knowledge of SQL and experience with relational databases.
• Experience in building and optimizing 'big data' pipelines, architectures, and datasets.
• Experience in incremental loading, ETL jobs operationalization, Data Migration,
• Proven history of manipulating, processing, and extracting value from large datasets, including building processes for data transformation, data structures, metadata, dependency, and workload management.
• Working knowledge of Master Data and Reference Data Management.
• Working knowledge of Data Modeling.
• Experience in developing and integrating Power BI reports and dashboards.
• Experience in supporting and collaborating with cross-functional teams in a dynamic environment.
• Working knowledge of building user interfaces using web technologies.
• Experience with the following software/tools:
• Azure cloud services- Microservices, APIs, Function, Databricks, ADF, LogicApp, AI Foundry.
• Relational SQL and NoSQL databases.
• Data pipeline and workflow management tools: Control-M, Airflow.
• Basic understanding of stream-processing systems: Storm, Spark-Streaming.
• Object-oriented/ scripting languages: Python, pySpark, Java, Scala.
• Basic knowledge of Data Science, LLMs, operationalization of AI solutions.
• Strong problem-solving abilities.
• Excellent verbal and written communication skills.

You are the heart & soul of Zurich!

At Zurich, we like to think outside the box and challenge the status quo. We take an optimistic approach by focusing on the positives and constantly asking What can go right?

We highly value the experience and know-how of our employees and offer a wide range of opportunities across business areas to encourage you to apply for new opportunities within Zurich when you are ready for your next career step.

People are Zurich’s most important asset. Their varied skills, perspectives and experiences drive innovation. And they reflect the breadth and diversity of our customers, suppliers, communities and investors around the world. We are committed to attracting and retaining talented individuals from a variety of backgrounds and experiences.