<\/span><\/span><\/div>Location: <\/span><\/span><\/b>Istanbul, Turkey<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/p>CEPRES<\/span><\/span><\/span><\/b> is the leading and fastest\-growing digital investment platform for private capital markets. Our global institutional client base benefits from our award\-winning investment solutions, which are delivered through the CEPRES platform connecting thousands of professionals worldwide.<\/span><\/span><\/span>
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<\/span><\/span>CEPRES <\/span><\/span><\/span><\/b>is headquartered in Munich, with staff in New York, Denver, Chicago, London, Heidelberg, and Singapore. Our team is incredibly diverse with over 20 nationalities in 6 different locations globally.<\/span><\/span><\/span>
<\/span><\/span><\/span><\/span><\/p>As a Data Engineer at CEPRES, you will work closely with the\nPrincipal and Senior Data Engineers to build and maintain data pipelines and\ninfrastructure. Alongside core data engineering responsibilities, you'll play a\nkey role in evaluating and annotating AI\-generated outputs related to ETL\nworkflows and data engineering systems, helping ensure the accuracy,\nreliability, and scalability of our data solutions. You'll also collaborate\nwith software engineering teams to help integrate the data layer with other\nplatform components.<\/span><\/span>
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<\/span><\/span><\/div>What You'll Do<\/span><\/span><\/b>
<\/span><\/span><\/p>- Develop,\n optimize, and maintain data pipelines using SQL and Python.<\/span>
<\/span><\/span><\/li>- Build\n and evaluate AI\-generated responses related to ETL/ELT workflows and data\n engineering systems.<\/span>
<\/span><\/span><\/li>- Assess\n AI outputs for data accuracy, pipeline reliability, scalability, and\n workflow efficiency.<\/span>
<\/span><\/span><\/li>- Assist\n in designing and implementing data systems and pipelines under the\n guidance of senior engineers.<\/span>
<\/span><\/span><\/li>- Maintain\n and optimize existing data structures, ensuring integration with software\n applications.<\/span>
<\/span><\/span><\/li>- Document\n data processes and adhere to data governance standards.<\/span>
<\/span><\/span><\/li>- Support\n the data engineering backlog and contribute to best\-practice\n implementation across projects.<\/span>
<\/span><\/span><\/li>- Participate\n in technical discussions and contribute ideas to improve our data\n architecture.<\/span>
<\/span><\/span><\/li>- Collaborate\n with software engineering teams and the Product team to ensure data\n solutions meet application needs.<\/span><\/span>
<\/li><\/ul><\/span>
Requirements<\/h3>Must\-Have Experience<\/span><\/span><\/b>
<\/span><\/span><\/div>- Background\n in Data Engineering, Computer Science, Information Systems, or related\n fields.<\/span>
<\/span><\/span><\/li>- 2\u20134\n years<\/span><\/span><\/b> of experience in Data Engineering (mid\-level).<\/span>
<\/span><\/span><\/li>- Hands\-on\n experience building data pipelines and performing data transformations in\n Python and Pyspark.<\/span>
<\/span><\/span><\/li>- Strong\n understanding of ETL/ELT processes, database systems, and data pipeline\n architecture.<\/span>
<\/span><\/span><\/li>- Solid\n knowledge of SQL (including writing efficient, optimized queries).<\/span>
<\/span><\/span><\/li>- Understanding\n data warehousing, workflow automation, and large\-scale data processing\n systems.<\/span>
<\/span><\/span><\/li>- Familiarity\n with version control (e.g., Git) and CI/CD concepts.<\/span>
<\/span><\/span><\/li>- Ability\n to work collaboratively with engineering teams and fast\-paced environment.<\/span>
<\/span><\/span><\/li>- Good\n communication and collaboration skills.<\/span>
<\/span><\/span><\/li>- Exposure\n to a major cloud platform (AWS, Azure, or GCP).<\/span>
<\/span><\/span><\/li>- Strong\n analytical, troubleshooting, and problem\-solving skills with attention to\n detail.<\/span>
<\/span><\/span><\/li><\/ul>Nice\-to\-Have<\/span><\/span><\/b>
<\/span><\/span><\/p>- Experience\n with Databricks.<\/span>
<\/span><\/span><\/li>- Experience\n with Snowflake.<\/span>
<\/span><\/span><\/li>- Exposure\n to AWS Services (Redshift, S3, Glue, Lambda).<\/span>
<\/span><\/span><\/li>- Familiarity\n with data visualization tools (Power BI).<\/span>
<\/span><\/span><\/li>- Experience\n with Docker, Jenkins, Octopus, or NoSQL databases.<\/span>
<\/span><\/span><\/li>- Experience\n with Azure DevOps / Azure Repo.<\/span>
<\/span><\/span><\/li><\/ul>Our Tech Stack<\/span><\/span><\/b>
<\/span><\/span><\/p>- Databricks<\/span>
<\/span><\/span><\/li>- Snowflake<\/span>
<\/span><\/span><\/li>- SQL\n Server<\/span>
<\/span><\/span><\/li>- AWS\n (Redshift, S3, Glue, Lambda)<\/span>
<\/span><\/span><\/li>- Azure\n DevOps<\/span>
<\/span><\/span><\/li>- Azure\n Repo<\/span>
<\/span><\/span><\/li>- Power\n BI<\/span>
<\/span><\/span><\/li>- Docker<\/span>
<\/span><\/span><\/li>- Jenkins<\/span>
<\/span><\/span><\/li>- Octopus<\/span><\/span>
<\/li><\/ul><\/span>
Benefits<\/h3>- Career Path in Private Equity<\/span><\/span><\/span><\/b> Step into one of the most in\-demand and exciting industries in finance today. With us, you'll experience unparalleled opportunities for career growth and promotions, receive regular feedback, and benefit from mentorship provided by an international team of passionate experts. Be part of a unique growth story and take on an exciting, challenging role in a dynamic global environment.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/li>- Culture That Drives Success <\/span><\/span><\/span><\/b>We are powered by core values that foster an entrepreneurial spirit, drive results, and empower ownership. At our company, collaboration and mutual support is at the heart of everything we do. Transparency in company goals ensures you\u2019re always part of the bigger picture.<\/span><\/span><\/span><\/span>
