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For Companies At a Glance
- Tasks: Design and maintain data pipelines, transform data, and create insightful dashboards.
- Company: Join a dynamic data team focused on driving business decisions through data.
- Benefits: Enjoy flexible work options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a collaborative culture that values innovation and impactful data solutions.
- Qualifications: Bachelor's or Master's in a related field with 3+ years of data engineering experience.
- Other info: Ideal for tech-savvy individuals eager to work with cutting-edge tools and technologies.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a skilled Data Engineer with expertise in Python development and Power BI to join our growing data team. The ideal candidate will be responsible for designing, building, and maintaining robust data pipelines, transforming raw data into clean datasets, and delivering compelling dashboards and insights to drive business decisions.
Key Responsibilities
- Design, develop, and optimize ETL/ELT pipelines using Python and SQL.
- Develop and maintain Power BI dashboards and reports to visualize data and track KPIs.
- Work with stakeholders to gather business requirements and translate them into technical solutions.
- Perform data wrangling, cleaning, and transformation to prepare datasets for analysis.
- Integrate data from multiple sources (APIs, databases, cloud storage).
- Ensure data quality, integrity, and security across systems.
- Collaborate with data analysts, scientists, and engineering teams to support advanced analytics.
- Monitor and improve pipeline performance, scalability, and reliability.
Required Skills
- Python for data engineering (e.g., pandas, NumPy, pyodbc, SQLAlchemy, etc.)
- Strong experience in Power BI (DAX, Power Query, data modeling, publishing dashboards)
- Advanced SQL skills (joins, CTEs, indexing, optimization)
- Experience with relational databases (e.g., SQL Server, PostgreSQL, MySQL)
- Understanding of ETL/ELT principles, data architecture, and data warehouse concepts
- Familiarity with APIs, RESTful services, and JSON/XML data handling
Preferred/Bonus Skills
- Experience with Azure Data Factory, Databricks, or AWS Glue
- Familiarity with CI/CD, version control (Git), and DevOps practices
- Knowledge of cloud platforms (Azure, AWS, or GCP)
- Basic understanding of data governance, security, and GDPR compliance
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field
- 3+ years of hands-on experience in data engineering roles
Soft Skills
- Strong analytical and problem-solving mindset
- Excellent communication and collaboration skills
- Ability to work independently and in cross-functional teams
Data Engineer - (Python and Power BI) employer: Natobotics
Contact Detail:
Natobotics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - (Python and Power BI)
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python libraries like pandas and NumPy, as well as Power BI. Having hands-on experience or projects showcasing these skills can significantly boost your chances.
✨Tip Number 2
Network with current or former employees of StudySmarter on platforms like LinkedIn. Engaging with them can provide insights into the company culture and the data team, which can be invaluable during interviews.
✨Tip Number 3
Prepare to discuss real-world examples of how you've designed and optimised ETL/ELT pipelines. Be ready to explain your thought process and the impact of your work on business decisions, as this aligns closely with the responsibilities of the role.
✨Tip Number 4
Showcase your ability to collaborate by preparing examples of past teamwork experiences, especially those involving cross-functional teams. Highlighting your communication skills will demonstrate that you can effectively work with stakeholders to gather requirements.
We think you need these skills to ace Data Engineer - (Python and Power BI)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, Power BI, and SQL. Include specific projects or achievements that demonstrate your skills in data engineering and pipeline optimisation.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and how your background aligns with the company's needs. Mention your experience with ETL/ELT processes and your ability to collaborate with stakeholders.
Showcase Relevant Projects: If you have worked on relevant projects, consider including a portfolio or links to your work. Highlight any dashboards you've created in Power BI or data pipelines you've built using Python.
Highlight Soft Skills: Don't forget to mention your soft skills such as problem-solving, communication, and teamwork. These are crucial for collaborating with data analysts and other teams within the company.
How to prepare for a job interview at Natobotics
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, Power BI, and SQL in detail. Bring examples of projects where you've designed ETL/ELT pipelines or created dashboards, as this will demonstrate your hands-on expertise.
✨Understand the Business Context
Research the company and its industry to understand how data drives their decisions. Be ready to discuss how you can translate business requirements into technical solutions, showcasing your ability to bridge the gap between stakeholders and technical teams.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical and problem-solving skills. Practice explaining your thought process when tackling data challenges, such as data wrangling or ensuring data quality, to illustrate your approach to real-world scenarios.
✨Demonstrate Collaboration Skills
Highlight your experience working in cross-functional teams. Share examples of how you've collaborated with data analysts, scientists, or other engineers, as this role requires strong communication and teamwork to support advanced analytics.
