At a Glance
- Tasks: Build and maintain scalable data pipelines using Python and Databricks.
- Company: Leading organisation in the energy and commodities sector.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with high-impact projects in a rapidly evolving sector.
- Why this job: Join a team transforming the energy landscape with cutting-edge data technology.
- Qualifications: 3-6 years in data engineering, strong Python and AWS skills required.
The predicted salary is between 60000 - 80000 £ per year.
We are working with a leading organisation in the energy and commodities sector, supporting the transition to a more sustainable and increasingly complex energy landscape.
As part of a growing Data Platform team, you will play a key role in building modern, scalable data infrastructure that supports analytics, trading insights, and operational decision-making. This role offers the opportunity to work on a cloud-native data platform using AWS and Databricks, handling large-scale datasets across trading, finance, and operational domains.
Key Responsibilities
- Build and maintain scalable ETL and ELT pipelines using Python and PySpark
- Ingest data from multiple source systems including trading, finance, and operational platforms
- Design and implement data transformations within a Databricks Lakehouse environment
- Work with AWS services such as S3, Kinesis, IAM, and Lambda to support data ingestion and processing
- Optimise Spark jobs for performance and cost efficiency
- Support the full data lifecycle from ingestion through to delivery
- Implement data quality checks to ensure accuracy and reliability of data
- Contribute to data governance standards and best practices
- Support the development of a secure and scalable data platform
- Work closely with analytics and BI teams to deliver high-quality datasets
- Support onboarding of new data sources and business areas
- Collaborate with engineering, operations, and business stakeholders
Requirements
- 3 to 6 years of experience in data engineering or analytics engineering
- Strong Python skills with experience using PySpark or Apache Spark
- Experience building and maintaining production-grade data pipelines
- Hands-on experience with Databricks, including Delta Lake and Lakehouse architecture
- Strong knowledge of AWS services such as S3, Kinesis, Lambda, or IAM
- Proficiency in SQL and data modelling
Desirable Experience
- Experience within energy, utilities, or commodities trading environments
- Exposure to streaming or real-time data pipelines
- Familiarity with CI/CD practices for data engineering workflows
This is an opportunity to work on high-impact data systems in a rapidly evolving sector, contributing to the build of a modern cloud-based data platform while working in a collaborative and technically strong environment.
Data Engineer employer: Cititec
Join a leading global commodities trading firm in London, where innovation meets impact. As a Forward Deployed Engineer, you'll thrive in a dynamic work culture that values collaboration and creativity, with ample opportunities for professional growth in AI and engineering. Enjoy the benefits of a hybrid working model, competitive compensation, and the chance to influence product direction while solving real business challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the energy and commodities sector on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Python, AWS, and Databricks. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ETL and ELT pipeline knowledge. Be ready to discuss your experience with Spark and AWS services. Practising coding challenges can also help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Engineers. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role and company culture.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your Python, AWS, and Databricks experience, and don’t forget to mention any relevant projects or achievements!
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 in energy and commodities makes you a great fit for us. Keep it concise but impactful!
Showcase Your Technical Skills:When filling out your application, be specific about your technical skills. Mention your experience with ETL/ELT pipelines, data transformations, and any AWS services you've worked with. We love seeing hands-on experience!
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 the role. Plus, it’s super easy to do!
How to prepare for a job interview at Cititec
✨Know Your Tech Stack
Make sure you brush up on your Python, AWS, and Databricks skills before the interview. Be ready to discuss specific projects where you've built ETL or ELT pipelines, and how you optimised Spark jobs for performance. This will show that you not only understand the tools but can also apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced in previous roles, especially related to data ingestion and processing. Think of examples where you implemented data quality checks or contributed to data governance standards. This will demonstrate your ability to tackle real-world problems in a data engineering context.
✨Understand the Industry
Since this role is in the energy and commodities sector, it’s beneficial to have a grasp of industry trends and challenges. Familiarise yourself with how data plays a role in trading and operational decision-making. This knowledge will help you connect your technical skills to the business needs during the interview.
✨Ask Insightful Questions
Interviews are a two-way street, so prepare some thoughtful questions about the team, the data platform, and the company's vision for the future. Asking about their approach to CI/CD practices or how they handle real-time data pipelines shows your genuine interest and helps you assess if the company is the right fit for you.
