data engineer for investment data in Berlin

Описание:

BIT Capital combines asset management expertise with the agility of a young tech company. Its investment products enable investors to participate in the growth of the technology-driven world. The company identifies emerging technology trends and investment opportunities on behalf of its investors.

Задачи:

• Build and improve internal products used by investment and research teams, including data pipelines, datasets, APIs, and tools




• Gather, triage, and prioritize requests from internal teams, maintain product integrity and consistency, and explain features and implementation trade-offs in non-technical language




• Design, build, and operate reliable data pipelines, ETLs, and integrations for complex financial and alternative datasets




• Reinforce engineering practices, including automated testing, CI/CD, pull requests, code reviews, and documentation




• Contribute to operational excellence through observability, monitoring, data quality, and secure data handling




• Use agentic AI for coding, review, testing, debugging, and documentation, and help advance these practices within the team

Требования:

• 3–5 Years of professional software or data engineering experience building and operating production systems




• Strong Python and SQL skills, clean and readable code, and a good understanding of data modelling




• Experience writing unit, integration, and data-quality tests; working with CI/CD; and using pull requests and code reviews




• Ability to explain technical work, its purpose, and limitations to non-engineers, and to say no constructively




• Hands-on use of AI across engineering functions, including coding systems such as Claude Code and Codex




• Genuine interest in investing, financial markets, and data, and ambition to develop in these areas




• Builder mindset, pragmatic trade-offs, attention to quality, and ability to work quickly without being careless




• Care for correctness, reliability, security, and long-term maintainability; ability to improve codebases and teams




• Curiosity about investment decisions and the data behind them




• Clear communication about progress, trade-offs, and risks, with end-to-end ownership of problems




• Candidates who prefer fully specified tickets and no user contact may not be suited to this role




• Candidates who use AI tools only occasionally may not be suited to this role

Будет плюсом: Databricks, PySpark, orchestration tools such as Airflow or Dagster, lakehouse formats such as Parquet, Delta, or Iceberg, AWS, investment or market data experience, internal-tool frontends or APIs, production LLM systems

Условия:

Work with petabytes of data and advanced tools in and beyond asset management, with Day 1 ownership of varied work and a steep learning curve

Join a team of around 40 professionals, including 20 financial-market experts, sector specialists, data engineers, and software developers; the team includes 15 nationalities

Work alongside experts in European asset management and interact directly with management and investors

Visa sponsorship and relocation support are available

Competitive compensation package with a variable component tied to fund performance

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