Data Engineer

About The Company:

WTW (NASDAQ: WTW) is in the business of people, risk and capital. With roots dating to 1828, our company has over 45,000 colleagues serving more than 140 countries and markets. Our values – client focus, teamwork, integrity, respect and excellence – underlie all that we do, including how we behave and interact with each other. They are part of our WTW DNA. We design and deliver solutions that manage risk, optimize benefits, cultivate talent, and expand the power of capital to protect and strengthen institutions and individuals. Our unique perspective allows us to see the critical intersections between talent, assets, and ideas — the dynamic formula that drives business performance. Together, we unlock potential. We are located on the internet at wtwco.com

Role and Responsibility:

• Build and maintain scalable pipelines with Azure Databricks, Python, and PySpark.
• Orchestrate data movement and workflows with ADF pipelines, triggers, and integration runtimes.
• Ingest and transform large datasets from sources such as SQL Server and Oracle.
• Manage data governance and access control with Unity Catalog.
• Implement cloud-native data solutions following best practices, with experience in the Azure or AWS cloud.
• Monitor, troubleshoot, and tune pipelines for performance and reliability; take part in the on-call rotation.
• Turn business requirements into robust data solutions and support production releases.
• Maintain documentation and runbooks.

Responsibilities

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Qualifications

Graduate

• Minimum 5 years of experience in Data Engineering, Data Warehousing, or related areas.
• Bachelor’s degree in Computer Science, Information Technology, or a related discipline or equivalent practical experience.
• Strong hands-on experience with Azure Databricks (jobs/workflows, Delta Lake, Unity Catalog) in enterprise-scale environments.
• Advanced Python skills and experience developing distributed data processing solutions using PySpark.
• Hands-on experience with Azure Data Factory pipelines and ETL/ELT design, development, and optimization.
• Strong understanding of Azure cloud services, networking and storage, data modeling, and SQL (T-SQL preferred).
• Working knowledge of Windows and Linux environments.
• Experience with CI/CD and DevOps practices for automated deployment of data solutions (GitHub Actions preferred).
• Proven ability to troubleshoot complex data processing and pipeline issues in production environments.