At a Glance
- Tasks: Build and optimise data models using Snowflake and dbt for impactful analytics.
- Company: Join HCLTech, a global leader in technology with a diverse workforce.
- Benefits: Enjoy competitive pay, health perks, and opportunities for remote work.
- Other info: Be part of a dynamic team with excellent career growth potential.
- Why this job: Make a difference by transforming complex data into high-performance solutions.
- Qualifications: 8-10 years of Snowflake expertise and strong SQL skills required.
The predicted salary is between 60000 - 80000 £ per year.
HCLTech is a global technology company, home to more than 220,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services.
Role: Snowflake Analytics Engineer
Experience Level Required in Years: 8-10 years
Mandatory Required Skills:
- Expert Snowflake knowledge and advanced dbt (Core/Cloud) experience.
- Modelling Concepts: Semantic Modelling, Dimensional Modelling (Kimball), Business/Logical/Physical Modelling.
- Skills: Software engineering mindset applied to SQL; git workflows, and automated testing.
Key Responsibilities:
- Build and maintain scalable modular data models using dbt inside Snowflake.
- Transition complex, unoptimised Teradata views into high-performance Snowflake tables.
- Implement data quality testing, version control (Git), and CI/CD pipelines for analytics code.
- Manage Snowflake warehouse optimization, access controls (ABAC), and query performance tuning.
Technical Requirements:
- Core Platforms: Expert Snowflake knowledge and advanced dbt (Core/Cloud) experience.
- Modeling Concepts: Semantic Modeling, Dimensional Modeling (Kimball), Business/Logical/Physical Modelling.
- Skills: Software engineering mindset applied to SQL; git workflows, and automated testing.
Snowflake Analytics Engineer in Slough employer: HCLTech
HCLTech is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among its diverse workforce of over 220,000 professionals. With a strong emphasis on employee growth, HCLTech provides extensive training opportunities and career advancement paths, particularly for roles like the Snowflake Analytics Engineer, ensuring that you can thrive in your career while working on cutting-edge technology solutions in a global environment.
StudySmarter Expert Advice🤫
We think this is how you could land Snowflake Analytics Engineer in Slough
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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 HCLTech!
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✨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 HCLTech.
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We think you need these skills to ace Snowflake Analytics Engineer in Slough
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 HCLTech, 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 HCLTech. 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 HCLTech
✨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 HCLTech!
✨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.
