At a Glance
- Tasks: Build and maintain data pipelines for Finance, automating workflows and ensuring data accuracy.
- Company: Engelhart, a dynamic commodities trading company with a collaborative culture.
- Benefits: Competitive salary, bonus plan, 25 days holiday, and robust health benefits.
- Other info: Inclusive environment promoting diversity and excellent career development opportunities.
- Why this job: Join a forward-thinking team and make an impact in the finance tech space.
- Qualifications: Strong Python and SQL skills, experience with AWS ETL pipelines, and finance process understanding.
The predicted salary is between 56700 - 69300 £ per year.
About Us
Engelhart was founded in 2013 by BTG Pactual Group as a commodities trading company.
Our business model is “asset light” and highly diversified – giving us the ability to adapt effectively and nimbly to changing market conditions.
We have assembled successful multidisciplinary teams, leveraging advanced fundamental analysis with deep quantitative and weather research capabilities.
Our activities are underpinned by strong risk management practices and by powerful technology and operational excellence.
We have exceptional teams with diverse global backgrounds and decades of experience, and are driven by a highly collaborative culture, across products and competencies.
In 2024, Engelhart acquired Trailstone, a global energy trading and technology company.
The acquisition provides us with new expertise, analytics and proprietary technology which is being used to provide risk management and optimisation services to help maximise the value of our clients’ renewable power.
The acquisition also expanded Engelhart’s capabilities into physical natural gas across North America, a critical fuel to support the energy transition.
Our talented and experienced individuals work together according to its four company values:
Performance, Agility, Collaboration, Entrepreneurship .
About the Role
As a Data Engineer within Engelhart's Finance department, you will build and operate reliable data pipelines connecting the data warehouse and CTRM platform with brokers and Futures Commission Merchants (FCMs), margin and collateral processes, and the wider Finance technology stack.
You will help automate manual Finance workflows into tested, monitored jobs, with robust reconciliations and controls that give stakeholders confidence in the completeness and accuracy of financial data.
This will be a full-time role based in our London office and owning the following responsibilities :
- Build, operate and maintain data pipelines between the data warehouse, CTRM platform, brokers and FCMs, margin and collateral processes, and Finance systems.
- Integrate data from the Finance stack, including P&L and F+, SAP General Ledger, Accounts Payable and Accounts Receivable, and bank statements.
- Automate manual Finance processes by developing reliable, tested and monitored jobs that can be operated and supported effectively.
- Implement reconciliations and data controls to identify missing or incomplete records, duplicates and breaks, and produce clear exception and break reporting.
- Ingest and process external files and feeds, including data received over SFTP and in formats such as CSV and XML.
- Investigate data and reconciliation issues, trace discrepancies through source systems and pipelines, and explain P&L or cash breaks to relevant Finance stakeholders.
- Develop and maintain serverless ETL solutions on AWS, using infrastructure as code and CI/CD practices to support consistent, controlled releases.
- Apply strong SQL and Python-based data processing to transform, validate and reconcile data accurately and efficiently.
- Work with Finance and technology stakeholders to understand requirements, improve existing workflows and deliver maintainable solutions with appropriate controls.
- Contribute to improving the reliability, observability and quality of Finance data flows as the business and its systems evolve.
About You
You will be a practical, analytical data engineer who combines strong software engineering skills with an understanding of Finance processes and controls.
You can work with varied data sources, investigate discrepancies and explain the cause of a P&L or cash break clearly.
You take ownership of the reliability of the jobs you build and look for opportunities to simplify and automate manual processes.
As a result, we believe the following experiences and skills are essential for application:
- Strong Python development skills, including experience with Pandas and/or Polars, Num Py, and automated testing with pytest.
- Hands-on experience building AWS serverless ETL pipelines, using services such as Lambda, Event Bridge, ECS/Fargate, Dynamo DB, Cloud Watch and S3.
- Experience with AWS Cloud Development Kit (CDK), infrastructure as code and CI/CD pipelines.
- Experience building APIs using Python frameworks, preferably Fast API.
- Strong SQL skills, including the ability to query, transform, validate and reconcile data.
- Experience ingesting external files and data feeds, including SFTP transfers and formats such as CSV and XML.
- Good understanding of Finance processes and data, with the analytical skills to investigate and clearly explain a P&L or cash break.
- A disciplined approach to testing, monitoring, reconciliation and control design, including checks for completeness, duplicates and exceptions.
- Strong problem-solving skills and attention to detail, with the ability to trace issues across systems and data pipelines.
- Clear communication skills and the ability to work effectively with Finance and technical stakeholders.
The following experience is not , but highly desirable for this role
- Experience using Kafka from Python.
- Experience integrating with SAP or treasury systems.
- Exposure to trading data, including positions and P&L.
- Familiarity with dbt and/or Airflow.
What we offer
- Competitive compensation and participation in Engelhart’s discretionary bonus plan.
- 25 days of annual holiday entitlement, excluding UK public holidays.
- Robust benefits package such as medical, dental, life insurance, generous pension contribution, and supplemental benefits partially subsidised by the Company.
- Eligibility to receive external and internal training in accordance with our Training & Development Policy.
We believe in inclusivity and are therefore dedicated to ensuring all employees – across gender identity, race, ethnicity, sexual orientation, religion, life experience, background and more – feel welcome and included in the company.
We promote diversity because we believe it is essential to our ability to think holistically.
Data Engineer, Finance in London employer: Engelhart
Engelhart is an exceptional employer, offering a dynamic and collaborative work culture that fosters innovation and professional growth. As part of our Commodity Trading Analytics Internship Program in London, interns will gain invaluable hands-on experience while working alongside seasoned professionals in a fast-paced environment, contributing to impactful projects that shape the future of commodities trading. With a commitment to inclusivity and diversity, we ensure that every team member feels valued and empowered to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer, Finance in 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 Engelhart!
✨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 Data Engineer, Finance at Engelhart.
✨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 Engelhart.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer, Finance at Engelhart, 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 Data Engineer, Finance in 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 Engelhart, 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 Engelhart. 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 Engelhart
✨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 Engelhart!
✨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.
