At a Glance
- Tasks: Build and optimise data pipelines using Python, SQL, and AWS services.
- Company: Join a forward-thinking tech company focused on data innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team culture with a focus on continuous learning and improvement.
- Why this job: Make an impact by developing scalable data solutions in a collaborative environment.
- Qualifications: Strong Python and SQL skills, with experience in AWS and Docker.
The predicted salary is between 60000 - 80000 £ per year.
Responsibilities
- Develop and maintain data pipelines using Python, SQL, and Apache Airflow.
- Containerise data applications and workflows using Docker.
- Build and optimise data solutions using AWS services including Redshift, Open Search, Lambda, Glue, Step Functions, and Batch.
- Collaborate with cross-functional teams to deliver robust, secure, and scalable data infrastructure.
- Manage version control using Git Lab (or similar).
- Monitor and troubleshoot data pipeline performance and reliability.
- Contribute to documentation and process improvement initiatives.
- Ensure data quality, governance, and security best practices are followed.
Requirements
- Strong programming skills in Python and proficiency in SQL.
- Experience with Apache Airflow for DAG orchestration and monitoring.
- Hands-on experience with Docker for containerisation.
- Proficient in AWS data services: Redshift, Open Search, Lambda, Glue, Step Functions, Batch.
- Familiarity with CI/CD pipelines and YAML-based configuration (e. g., Git Lab CI/CD).
- Proficient in Git and collaborative development using Git Lab (or similar).
- Understanding of AWS security best practices, IAM policies, and RBAC.
• Desirable Skills
- Experience with AWS services such as Athena, SQS, Cloud Watch, Cloud Trail, EMR.
- Exposure to infrastructure-as-code tools (e. g., Terraform, Cloud Formation).
- Familiarity with documentation tools like Confluence and README standards.
- Experience working in consulting or client-facing environments.
- Strong problem-solving and troubleshooting abilities.
- Comfortable working in Agile environments.
- Effective stakeholder management and communication skills.
- Collaborative mindset and willingness to share knowledge.
- #J-18808-Ljbffr
StudySmarter Expert Advice🤫
We think this is how you could land AWS 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 Jobtailor!
✨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 AWS Data Engineer at Jobtailor.
✨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 Jobtailor.
✨Apply Directly through Our Website
When you find a suitable opening like AWS Data Engineer at Jobtailor, 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 AWS 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 Jobtailor, 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 Jobtailor. 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 Jobtailor
✨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 Jobtailor!
✨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.
