At a Glance
- Tasks: Build and optimise data models using Snowflake and dbt for high performance.
- Company: Join HCLTech, a global leader in technology with a diverse workforce.
- Benefits: Enjoy remote work flexibility, competitive salary, and career development opportunities.
- Other info: Be part of a dynamic team with a focus on innovation and growth.
- Why this job: Make an impact by transforming data solutions for major industries.
- Qualifications: Experience in SQL, git workflows, and automated testing 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
- Skills: Software engineering mindset applied to SQL; git workflows, and automated testing.
- Build and maintain scalable modular data models using dbt inside Snowflake.
- Transition complex, unoptimised Teradata views into high-performance Snowflake.
- Implement data quality testing, version control (Git), and CI/CD pipelines for performance tuning.
Skills: Software engineering mindset applied to SQL; automated testing.
Senior Engineer - Remote in City of London employer: HCLTech
HCLTech is an exceptional employer that fosters a dynamic and inclusive work culture, offering remote opportunities that empower employees to thrive in their roles. With a strong focus on professional development, employees benefit from continuous learning and growth opportunities, while being part of a global team that values innovation and collaboration. Joining HCLTech means being at the forefront of technology advancements, working with diverse clients across various industries, and contributing to impactful projects that shape the future.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer - Remote in City of London
✨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 HCLTech!
✨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 Engineer - Remote at HCLTech.
✨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.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Engineer - Remote at HCLTech, 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 Engineer - Remote in City of London
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.
