ꯊꯕꯛ꯫
ꯄꯥꯔꯇꯅꯔ ꯐꯤꯗꯇꯒꯤ꯫
Software Engineer, Data
ꯔꯤꯛꯕꯦꯁ꯭ꯠ ꯇꯧꯔꯕꯥ ꯃꯇꯨꯡꯗꯥ ꯃꯃꯜ꯫
ꯑꯀꯨꯞꯄꯥ ꯃꯔꯣꯂꯁꯤꯡ꯫
- ꯊꯕꯛ ꯄꯤꯕꯒꯤ ꯃꯈꯜ꯫
- ꯐꯨꯜ ꯇꯥꯏꯝ ꯑꯣꯏꯅꯥ ꯊꯕꯛ ꯇꯧꯕꯥ꯫
- ꯔꯤꯃꯣꯠ ꯇꯧꯕꯥ꯫
- ꯅꯪ
- ꯀꯝꯄꯦꯅꯤ ꯑꯁꯤꯅꯥ ꯑꯦꯟ.ꯗꯤ.ꯑꯦ
- engelhart
ꯃꯁꯛ ꯈꯪꯗꯣꯀꯄꯥ꯫
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 member of the Data team, you will help build the services, infrastructure, and data platforms that power our business. Our team is responsible for ingesting, processing, storing, and distributing large volumes of data reliably and efficiently, enabling teams across the business to make data-driven decisions and build innovative products.
This role sits at the intersection of backend software engineering and data engineering, with an emphasis on data engineering. You will build and maintain data pipelines, develop backend services for data ingestion and access, and contribute to the data infrastructure that enables reliable, cost-effective, and high-performance data processing.
You'll work closely with software engineers, DevOps engineers, product managers, data consumers, and more experienced colleagues, who will provide guidance, code reviews, and support as you grow. While the role involves technical collaboration across the organization, it is primarily focused on engineering rather than stakeholder management.
We are a trading company, so business requirements change quickly, and priorities can shift. We are looking for someone who enjoys solving technical problems, takes ownership of their work, is eager to learn, and makes pragmatic engineering decisions in a dynamic environment.
Responsibilities
• Build and maintain reliable data pipelines and ingestion workflows for structured and unstructured data from a variety of internal and external sources, including fetching data from external providers.
• Develop and maintain backend services and APIs (e.g., FastAPI ) that support data ingestion, processing, and distribution, including asynchronous ingestion at scale.
• Transform and process data using Python and Pandas.
• Contribute to reusable frameworks and tooling that simplify onboarding new data sources and improve developer productivity.
• Work with data lakes, analytical and relational databases, and contribute to their design and optimization together with senior colleagues.
• Help catalogue and document the data we own so it can be discovered and used by others.
• Help improve the reliability, scalability, observability, and cost-efficiency of our data infrastructure.
• Integrate data across multiple systems while reducing duplication and ensuring high data quality.
• Contribute to orchestration workflows and automated data processing pipelines.
• Build internal libraries and services that enable other engineering teams to access and consume data efficiently.
• Monitor, troubleshoot, and fix issues in production systems and data pipelines, escalating when needed.
• Participate in architecture discussions and technical decisions across the data platform.
• Collaborate with software engineers, DevOps engineers, product managers, and data consumers to deliver high-impact solutions.
• Build and maintain simple internal self-service tools, occasionally including a user interface.
• Use AI coding assistants (e.g., GitHub Copilot) responsibly to speed up development, while remaining accountable for the design, correctness, and quality of your code.
• Identify opportunities to simplify systems, improve automation, and reduce operational overhead.
About You
The following education, experience, and skills are essential for this role:
• Background in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.
• Around 2+ years of professional experience in data engineering or backend development, with a focus on data pipelines and data-intensive systems.
• Professional experience developing applications and services using Python, including data processing with Pandas or similar libraries.
• Experience building or working with data pipelines (ETL/ELT) or data processing systems.
• Solid SQL skills and experience working with relational databases (e.g., PostgreSQL, SQL Server).
• Experience building RESTful APIs and backend services.
• Familiarity with containerized applications (e.g., Docker) and basic software delivery practices such as Git and CI/CD.
• Hands-on grounding in software engineering fundamentals: software design principles, programming paradigms, testing, and maintainability. You must be able to write, read, debug, and reason about code yourself.
• Experience using AI coding assistants (e.g., GitHub Copilot) as a tool to work faster, including prompting them effectively and critically reviewing their output. AI supports your work; it does not replace your own engineering judgement.…
Source: Arbeitnow (https://www.arbeitnow.com/jobs/companies/engelhart/software-engineer-data-berlin-351586)
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 member of the Data team, you will help build the services, infrastructure, and data platforms that power our business. Our team is responsible for ingesting, processing, storing, and distributing large volumes of data reliably and efficiently, enabling teams across the business to make data-driven decisions and build innovative products.
This role sits at the intersection of backend software engineering and data engineering, with an emphasis on data engineering. You will build and maintain data pipelines, develop backend services for data ingestion and access, and contribute to the data infrastructure that enables reliable, cost-effective, and high-performance data processing.
You'll work closely with software engineers, DevOps engineers, product managers, data consumers, and more experienced colleagues, who will provide guidance, code reviews, and support as you grow. While the role involves technical collaboration across the organization, it is primarily focused on engineering rather than stakeholder management.
We are a trading company, so business requirements change quickly, and priorities can shift. We are looking for someone who enjoys solving technical problems, takes ownership of their work, is eager to learn, and makes pragmatic engineering decisions in a dynamic environment.
Responsibilities
• Build and maintain reliable data pipelines and ingestion workflows for structured and unstructured data from a variety of internal and external sources, including fetching data from external providers.
• Develop and maintain backend services and APIs (e.g., FastAPI ) that support data ingestion, processing, and distribution, including asynchronous ingestion at scale.
• Transform and process data using Python and Pandas.
• Contribute to reusable frameworks and tooling that simplify onboarding new data sources and improve developer productivity.
• Work with data lakes, analytical and relational databases, and contribute to their design and optimization together with senior colleagues.
• Help catalogue and document the data we own so it can be discovered and used by others.
• Help improve the reliability, scalability, observability, and cost-efficiency of our data infrastructure.
• Integrate data across multiple systems while reducing duplication and ensuring high data quality.
• Contribute to orchestration workflows and automated data processing pipelines.
• Build internal libraries and services that enable other engineering teams to access and consume data efficiently.
• Monitor, troubleshoot, and fix issues in production systems and data pipelines, escalating when needed.
• Participate in architecture discussions and technical decisions across the data platform.
• Collaborate with software engineers, DevOps engineers, product managers, and data consumers to deliver high-impact solutions.
• Build and maintain simple internal self-service tools, occasionally including a user interface.
• Use AI coding assistants (e.g., GitHub Copilot) responsibly to speed up development, while remaining accountable for the design, correctness, and quality of your code.
• Identify opportunities to simplify systems, improve automation, and reduce operational overhead.
About You
The following education, experience, and skills are essential for this role:
• Background in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.
• Around 2+ years of professional experience in data engineering or backend development, with a focus on data pipelines and data-intensive systems.
• Professional experience developing applications and services using Python, including data processing with Pandas or similar libraries.
• Experience building or working with data pipelines (ETL/ELT) or data processing systems.
• Solid SQL skills and experience working with relational databases (e.g., PostgreSQL, SQL Server).
• Experience building RESTful APIs and backend services.
• Familiarity with containerized applications (e.g., Docker) and basic software delivery practices such as Git and CI/CD.
• Hands-on grounding in software engineering fundamentals: software design principles, programming paradigms, testing, and maintainability. You must be able to write, read, debug, and reason about code yourself.
• Experience using AI coding assistants (e.g., GitHub Copilot) as a tool to work faster, including prompting them effectively and critically reviewing their output. AI supports your work; it does not replace your own engineering judgement.…
Source: Arbeitnow (https://www.arbeitnow.com/jobs/companies/engelhart/software-engineer-data-berlin-351586)
ꯂꯤꯁ꯭ꯠ ꯑꯁꯤ ꯄꯥꯔꯇꯅꯔ ꯐꯤꯗ ꯑꯃꯗꯒꯤ ꯂꯥꯀꯏ꯫ ꯁꯣꯔꯁ ꯋꯦꯕꯁꯥꯏꯠꯇꯥ ꯑꯦꯞꯂꯥꯏ ꯇꯧꯕꯤꯌꯨ꯫
ꯁꯣꯔꯁ꯫: engelhart
ꯃꯐꯝ꯫
ꯕꯔꯂꯤꯟ, ꯖꯔꯃꯅꯤꯗꯥ ꯂꯩꯕꯥ ꯌꯨ.ꯑꯦꯁ
engelhartꯅꯥ ꯄꯤꯕꯥ ꯂꯤꯁ꯭ꯠ꯫
