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For Companies At a Glance
- Tasks: Design and optimise data pipelines using cutting-edge Azure technologies.
- Company: Join WTW, a forward-thinking tech company in Woodbridge.
- Benefits: Enjoy competitive salary, flexible work, and career growth opportunities.
- Why this job: Work with the latest cloud and AI tech while making a real impact.
- Qualifications: 5+ years in data engineering with strong skills in Azure and SQL.
- Other info: Collaborative team environment that values innovation and diversity.
The predicted salary is between 36000 - 60000 £ per year.
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‑tying 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.
Qualifications
What You Bring to the Table
- 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.
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Senior Data Engineer employer: WTW
Contact Detail:
WTW Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even local tech events. The more people you know, the better your chances of landing that Senior Data Engineer role.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your data pipelines, transformations, or any cool projects you've worked on. This will make you stand out when applying through our website.
✨Ace the Interview
Prepare for technical interviews by brushing up on your SQL and programming skills. Practice common data engineering problems and be ready to discuss how you've tackled challenges in past roles. Confidence is key!
✨Follow Up
After an interview, don’t forget to send a thank-you email! It shows your enthusiasm for the role and keeps you fresh in their minds. Plus, it’s a great way to reiterate why you’re the perfect fit for the team.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with Azure and data pipelines, and don’t forget to mention any relevant projects that showcase your skills in data engineering.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you’re passionate about data engineering and how your background aligns with our needs. Be specific about your experience with tools like PySpark and Azure Synapse.
Showcase Your Problem-Solving Skills: We love problem solvers! In your application, include examples of challenges you've faced in data engineering and how you tackled them. This will help us see your innovative side and how you approach complex issues.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at WTW
✨Know Your Tech Stack
Make sure you’re well-versed in Azure Synapse, Azure Data Factory, and PySpark. Brush up on your SQL skills and be ready to discuss how you've used these tools in past projects. Being able to talk about specific examples will show that you’re not just familiar with the tech, but that you can actually apply it.
✨Showcase Your Problem-Solving Skills
Prepare to discuss challenges you've faced in data engineering and how you overcame them. Think of a couple of scenarios where you had to troubleshoot ETL/ELT workflows or optimise data pipelines. This will demonstrate your ability to think critically and innovate, which is exactly what they’re looking for.
✨Collaborate Like a Pro
Since this role involves working with Data Scientists and AI Engineers, be ready to talk about your experience collaborating with cross-functional teams. Share examples of how you’ve contributed to data-driven solutions and how you ensure everyone is on the same page. Teamwork is key!
✨Stay Ahead of the Curve
Familiarise yourself with emerging cloud and AI technologies. Mention any recent trends or tools you’ve been exploring, especially those related to real-time data streaming or CI/CD practices. Showing that you’re proactive about learning will impress them and align with their forward-thinking culture.
