Overview

The Role:

• Designing, building, and optimizing data pipelines, data transformations, data storage functions, for data consumption using Azure Synapse, Azure Data Factory, and Azure Fabric.
• Writing and fine-tuning PySpark notebooks to handle massive data workloads efficiently.
• Troubleshooting and enhancing ETL/ELT workflows in Azure Synapse.
• Managing and organizing Data Lakes to ensure seamless data access and performance.
• Integrating AI/LLM models into data pipelines to drive innovation and insights.
• Collaborating with Data Scientists, AI Engineers, and Analysts to create powerful data-driven solutions.
• Ensuring data security, governance, and compliance within our Azure ecosystem.
• Staying ahead of the curve with emerging cloud, AI, and big data technologies.

Responsibilities

• As part of the role, design, build, and optimize data pipelines and related data storage and transformation components for data consumption using Azure Synapse, Azure Data Factory, and Azure Fabric.
• Develop and optimize PySpark notebooks for large-scale data processing.
• Troubleshoot and enhance ETL/ELT workflows within Azure Synapse.
• Organize and manage Data Lakes to ensure data is accessible and performs well for analytics.
• Integrate AI/LLM models into data pipelines to enable innovative data-driven solutions.
• Collaborate with Data Scientists, AI Engineers, and Analysts to deliver impactful data products.
• Maintain data security, governance, and regulatory compliance within the Azure environment.
• Keep up-to-date with cloud, AI, and big data technologies and best practices.

Qualifications

• 5+ years of experience in data engineering, working with large-scale data platforms and cloud-based data architectures.
• Proven hands-on experience designing, building, and optimizing data pipelines in at least one major cloud platform (Azure, AWS, or Google Cloud Platform).
• Expertise in modern data engineering tools and frameworks, such as Databricks, Apache Spark/PySpark, Azure Synapse, AWS Glue, or Google Cloud Dataflow.
• Strong proficiency in SQL and one or more programming languages (Python, Scala, or Java).
• Experience with orchestration and workflow management tools (e.g., Airflow, Data Factory, Cloud Composer).
• Hands-on experience with data management within data lake architectures, data warehousing, and big data processing functions.
• Familiarity with the integration and deployment of AI/ML and LLM solutions into data pipelines is a plus.

Bonus Points If You Have

• Experience with real-time data streaming tools (e.g., Kafka, Kinesis, Pub/Sub).
• Knowledge of CI/CD practices for data engineering (e.g., DevOps pipelines, infrastructure as code).
• Background in insurance, risk, or financial services a plus.
• Familiarity with Databricks and its integration with Azure Synapse.
• Knowledge of Graph Databases and NoSQL technologies.

Why You’ll Love Working Here

• Work with the latest cloud and AI technologies, always stay ahead of the game.
• Be part of a collaborative and forward-thinking team that values your ideas.
• Competitive salary, benefits, and plenty of opportunities to grow your career.
• A flexible, modern work environment designed for how people work today.

We’re not just looking for someone to check off the skills list, we want a problem solver, an innovator, and someone who loves working with data. If this sounds like you, hit us up!

At WTW, we believe difference makes us stronger. We want our workforce to reflect the different and varied markets we operate in and to build a culture of inclusivity that makes colleagues feel welcome, valued and empowered to bring their whole selves to work every day. We are an equal opportunity employer committed to fostering an inclusive work environment throughout our organisation. We embrace all types of diversity.