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- Tasks: Architect and build robust data systems while analysing and preparing data for insights.
- Company: Join BI:PROCSI, a rapidly expanding company with a focus on innovation and personal growth.
- Benefits: Enjoy a fantastic culture, work-life balance, and comprehensive benefits including health and pension.
- Other info: Dynamic team environment with opportunities for continuous learning and career advancement.
- Why this job: Make an impact with cutting-edge technology and work with world-class clients in a remote-first environment.
- Qualifications: Strong SQL, Python skills, and experience with cloud technologies and data modelling techniques.
The predicted salary is between 60000 - 80000 £ per year.
Location: Mostly Remote, with a requirement to work from London once every two weeks. Must have a Right to Work in the UK.
Overview: As a Senior Data Engineer at BI:PROCSI, you’ll play a crucial role in storing, processing, modelling, and applying data science to make data and insights available for analytics and business intelligence (BI) systems. This position offers a unique opportunity to work with cutting‑edge products and world‑class clients in a remote‑first environment.
Key Responsibilities:
- Architect and build robust data systems and pipelines
- Analyse, organise, and prepare raw data for modelling and analytics
- Evaluate business needs and objectives
- Combine raw information from diverse sources
- Enhance data quality and reliability
- Identify opportunities for data acquisition
- Develop analytical reports using data science techniques
Required Skills:
- Strong data modelling and SQL/database design skills
- Proficiency in ETL/ELT processes
- Expert‑level SQL and Python programming
- Understanding of different data modelling techniques (e.g. Kimball, star and snowflake schemas)
- Cloud and Big Data Technologies
- Familiarity with cloud data warehouses (AWS, Azure, GCP, or Snowflake)
- Experience designing and building Agentic AI systems using models such as Claude, OpenAI (GPT), or similar LLM frameworks
- Experience deploying AI solutions into production environments with scalability and reliability in mind
- Knowledge of CI/CD pipelines for deploying AI/ML or data products
- Experience using tools such as JIRA or Asana for project tracking and delivery
- Familiarity with data pipeline and integration tools (e.g. Airflow, Fivetran, Matillion, or similar)
- Comfortable working within Agile delivery environments
Why Choose BI:PROCSI?
- BI:PROCSI offers a unique work environment focused on innovation and personal growth.
- A phenomenal company culture that values diversity and work‑life balance
- Opportunities for continuous learning and career advancement
- Comprehensive benefits package, including Vitality Health and Nest Pension
Join our team of passionate innovators and contribute to our mission of being the benchmark for excellence and quality of service in everything we do.
Senior Data Engineer employer: BI:PROCSI
Contact Detail:
BI:PROCSI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at BI:PROCSI on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your data engineering projects. This is your chance to demonstrate your expertise in SQL, Python, and cloud technologies.
✨Tip Number 3
Ace the interview! Research common data engineering interview questions and practice your answers. Be ready to discuss your experience with ETL processes and data modelling techniques.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our innovative team at BI:PROCSI.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your data modelling, SQL, and Python expertise, and don’t forget to mention any cloud technologies you’ve worked with!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how your background aligns with our mission at BI:PROCSI. Keep it concise but impactful!
Showcase Your Projects: If you've worked on relevant projects, whether in a professional or personal capacity, make sure to include them. We love seeing real-world applications of your skills, especially with AI systems or data pipelines!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at BI:PROCSI
✨Know Your Data Inside Out
Before the interview, brush up on your data modelling skills and be ready to discuss different techniques like Kimball and star schemas. Be prepared to share examples of how you've architected data systems in the past, as this will show your expertise and confidence.
✨Showcase Your Technical Skills
Make sure you can demonstrate your proficiency in SQL and Python during the interview. Prepare to solve a few coding challenges or answer technical questions that highlight your experience with ETL/ELT processes and cloud technologies like AWS or Azure.
✨Understand the Business Needs
Familiarise yourself with BI:PROCSI's mission and the types of clients they work with. Think about how your role as a Senior Data Engineer can directly impact their business objectives and be ready to discuss how you can enhance data quality and reliability for their analytics.
✨Be Agile and Collaborative
Since the company values Agile delivery, be prepared to talk about your experience working in Agile environments. Share examples of how you've used tools like JIRA or Asana for project tracking and how you collaborate with teams to deliver data solutions effectively.