About the role

<div class="content-intro"><h2>About Us</h2>
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.</div><h3>About the Role </h3>
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: 
<ul>
<li>Build, operate and maintain data pipelines between the data warehouse, CTRM platform, brokers and FCMs, margin and collateral processes, and Finance systems. </li>
<li>Integrate data from the Finance stack, including P&L and F+, SAP General Ledger, Accounts Payable and Accounts Receivable, and bank statements. </li>
<li>Automate manual Finance processes by developing reliable, tested and monitored jobs that can be operated and supported effectively. </li>
<li>Implement reconciliations and data controls to identify missing or incomplete records, duplicates and breaks, and produce clear exception and break reporting. </li>
<li>Ingest and process external files and feeds, including data received over SFTP and in formats such as CSV and XML. </li>
<li>Investigate data and reconciliation issues, trace discrepancies through source systems and pipelines, and explain P&L or cash breaks to relevant Finance stakeholders. </li>
<li>Develop and maintain serverless ETL solutions on AWS, using infrastructure as code and CI/CD practices to support consistent, controlled releases. </li>
<li>Apply strong SQL and Python-based data processing to transform, validate and reconcile data accurately and efficiently. </li>
<li>Work with Finance and technology stakeholders to understand requirements, improve existing workflows and deliver maintainable solutions with appropriate controls. </li>
<li>Contribute to improving the reliability, observability and quality of Finance data flows as the business and its systems evolve. </li>
</ul>
 
<h3>About You </h3>
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: 
<ul>
<li>Strong Python development skills, including experience with Pandas and/or Polars, NumPy, and automated testing with pytest. </li>
<li>Hands-on experience building AWS serverless ETL pipelines, using services such as Lambda, EventBridge, ECS/Fargate, DynamoDB, CloudWatch and S3. </li>
<li>Experience with AWS Cloud Development Kit (CDK), infrastructure as code and CI/CD pipelines. </li>
<li>Experience building APIs using Python frameworks, preferably FastAPI. </li>
<li>Strong SQL skills, including the ability to query, transform, validate and reconcile data. </li>
<li>Experience ingesting external files and data feeds, including SFTP transfers and formats such as CSV and XML. </li>
<li>Good understanding of Finance processes and data, with the analytical skills to investigate and clearly explain a P&L or cash break. </li>
<li>A disciplined approach to testing, monitoring, reconciliation and control design, including checks for completeness, duplicates and exceptions. </li>
<li>Strong problem-solving skills and atten

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Data Engineer, Finance

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