At a Glance
- Tasks: Design and optimise data pipelines using Snowflake and Python for enterprise analytics.
- Company: Leading tech firm focused on innovative data solutions.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on mentorship and career advancement.
- Why this job: Join a dynamic team and shape the future of data engineering.
- Qualifications: 8-15 years in data engineering with expertise in Snowflake and cloud technologies.
The predicted salary is between 63000 - 77000 £ per year.
Role Summary
- We are seeking a highly skilled
- Senior Data Engineer with 8â
15 years of experience in designing, developing, and implementing enterprise-scale data solutions. The ideal candidate will possess strong expertise in
Snowflake and hands-on experience with
Python, Py Spark, AWS, and Airflow for building scalable, high-performance data platforms.
The role demands strong technical leadership, problem-solving capabilities, and the ability to collaborate effectively with cross-functional teams to deliver robust data engineering solutions.
Key Responsibilities
- Design, develop, and optimize data pipelines and data models using Snowflake for enterprise analytics and reporting
- Write and optimize complex SQL / PLâ
- SQL queries, procedures, and transformations to support largeâ scale data processing
- Build and optimize enterprise data warehouse solutions on Snowflake.
- Develop data ingestion, transformation, and orchestration workflows using Python, Py Spark, and Airflow.
- Develop and optimize complex SQL queries, stored procedures, views, streams, and tasks in Snowflake.
- Implement scalable cloud-based data solutions leveraging AWS services.
- Ensure data quality, governance, security, and compliance across the data platform.
- Perform query tuning, performance optimization, and cost optimization within Snowflake.
- Automate deployment and monitoring through CI/CD and Dev Ops practices.
- Collaborate with business stakeholders, architects, analysts, and engineering teams to translate business requirements into technical solutions.
- Troubleshoot production issues and implement preventive measures to enhance platform reliability.
- Preferred Experience
- Experience in large-scale cloud data migration initiatives.
- Strong understanding of enterprise data architecture and modern data platforms.
- Experience working with structured, semi-structured, and unstructured data.
- Exposure to Banking, Financial Services, or other large enterprise environments will be an added advantage.
- Experience in leading technical discussions and mentoring engineering teams.
Senior Data Engineer employer: Test Triangle
As an IoT Data Architect at our company, you will thrive in a dynamic and innovative environment that prioritises employee growth and collaboration. We offer competitive benefits, a supportive work culture, and opportunities to work on cutting-edge projects in regulated sectors, ensuring your contributions are both meaningful and impactful. Join us to be part of a team that values your expertise and fosters professional development in a location known for its vibrant tech community.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Test Triangle!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer at Test Triangle.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Test Triangle.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer at Test Triangle, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Test Triangle, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Test Triangle. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Test Triangle
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Test Triangle!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
