Data Engineer (f/m/x)

Location: Istanbul, TurkeyCEPRES 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. CEPRES 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.As a Data Engineer at CEPRES, you will work closely with the Principal and Senior Data Engineers to build and maintain data pipelines and infrastructure. Alongside core data engineering responsibilities, you'll play a key role in evaluating and annotating AI-generated outputs related to ETL workflows and data engineering systems, helping ensure the accuracy, reliability, and scalability of our data solutions. You'll also collaborate with software engineering teams to help integrate the data layer with other platform components.What You'll DoDevelop, optimize, and maintain data pipelines using SQL and Python.Build and evaluate AI-generated responses related to ETL/ELT workflows and data engineering systems.Assess AI outputs for data accuracy, pipeline reliability, scalability, and workflow efficiency.Assist in designing and implementing data systems and pipelines under the guidance of senior engineers.Maintain and optimize existing data structures, ensuring integration with software applications.Document data processes and adhere to data governance standards.Support the data engineering backlog and contribute to best-practice implementation across projects.Participate in technical discussions and contribute ideas to improve our data architecture.Collaborate with software engineering teams and the Product team to ensure data solutions meet application needs.RequirementsMust-Have ExperienceBackground in Data Engineering, Computer Science, Information Systems, or related fields.2–4 years of experience in Data Engineering (mid-level).Hands-on experience building data pipelines and performing data transformations in Python and Pyspark.Strong understanding of ETL/ELT processes, database systems, and data pipeline architecture.Solid knowledge of SQL (including writing efficient, optimized queries).Understanding data warehousing, workflow automation, and large-scale data processing systems.Familiarity with version control (e.g., Git) and CI/CD concepts.Ability to work collaboratively with engineering teams and fast-paced environment.Good communication and collaboration skills.Exposure to a major cloud platform (AWS, Azure, or GCP).Strong analytical, troubleshooting, and problem-solving skills with attention to detail.Nice-to-HaveExperience with Databricks.Experience with Snowflake.Exposure to AWS Services (Redshift, S3, Glue, Lambda).Familiarity with data visualization tools (Power BI).Experience with Docker, Jenkins, Octopus, or NoSQL databases.Experience with Azure DevOps / Azure Repo.Our Tech StackDatabricksSnowflakeSQL ServerAWS (Redshift, S3, Glue, Lambda)Azure DevOpsAzure RepoPower BIDockerJenkinsOctopusBenefitsCareer Path in Private Equity 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.Culture That Drives Success 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’re always part of the bigger picture.Commitment to Our People We care deeply about our team, offering outstanding benefits and opportunities to thrive in a diverse, inclusive, and international workplace.Compensation of attractive package that reflects your skills, contributions, and growth potential.At CEPRES, we're committed to creating an inclusive environment for all. We celebrate diversity and encourage applicants from all backgrounds, experiences, and perspectives to apply.Location: Istanbul, TurkeyCEPRES 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. CEPRES 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.As a Data Engineer at CEPRES, you will work closely with the Principal and Senior Data Engineers to build and maintain data pipelines and infrastructure. Alongside core data engineering responsibilities, you'll play a key role in evaluating and annotating AI-generated outputs related to ETL workflows and data engineering systems, helping ensure the accuracy, reliability, and scalability of our data solutions. You'll also collaborate with software engineering teams to help integrate the data layer with other platform components.What You'll DoDevelop, optimize, and maintain data pipelines using SQL and Python.Build and evaluate AI-generated responses related to ETL/ELT workflows and data engineering systems.Assess AI outputs for data accuracy, pipeline reliability, scalability, and workflow efficiency.Assist in designing and implementing data systems and pipelines under the guidance of senior engineers.Maintain and optimize existing data structures, ensuring integration with software applications.Document data processes and adhere to data governance standards.Support the data engineering backlog and contribute to best-practice implementation across projects.Participate in technical discussions and contribute ideas to improve our data architecture.Collaborate with software engineering teams and the Product team to ensure data solutions meet application needs.

Location: Istanbul, Turkey

Location: Istanbul, TurkeyLocation: Istanbul, TurkeyLocation: Istanbul, TurkeyLocation:Location:Location:Istanbul, TurkeyIstanbul, TurkeyCEPRES 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.CEPRESCEPRESCEPRESCEPRESis 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.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.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.

CEPRES 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.

CEPRES 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.CEPRES 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.CEPRESCEPRESCEPRESCEPRESis 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.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.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.As a Data Engineer at CEPRES, you will work closely with the Principal and Senior Data Engineers to build and maintain data pipelines and infrastructure. Alongside core data engineering responsibilities, you'll play a key role in evaluating and annotating AI-generated outputs related to ETL workflows and data engineering systems, helping ensure the accuracy, reliability, and scalability of our data solutions. You'll also collaborate with software engineering teams to help integrate the data layer with other platform components.As a Data Engineer at CEPRES, you will work closely with the Principal and Senior Data Engineers to build and maintain data pipelines and infrastructure. Alongside core data engineering responsibilities, you'll play a key role in evaluating and annotating AI-generated outputs related to ETL workflows and data engineering systems, helping ensure the accuracy, reliability, and scalability of our data solutions. You'll also collaborate with software engineering teams to help integrate the data layer with other platform components.As a Data Engineer at CEPRES, you will work closely with the Principal and Senior Data Engineers to build and maintain data pipelines and infrastructure. Alongside core data engineering responsibilities, you'll play a key role in evaluating and annotating AI-generated outputs related to ETL workflows and data engineering systems, helping ensure the accuracy, reliability, and scalability of our data solutions. You'll also collaborate with software engineering teams to help integrate the data layer with other platform components.

What You'll Do

What You'll DoWhat You'll DoWhat You'll Do

• Develop, optimize, and maintain data pipelines using SQL and Python.

Develop, optimize, and maintain data pipelines using SQL and Python.Develop, optimize, and maintain data pipelines using SQL and Python.

• Build and evaluate AI-generated responses related to ETL/ELT workflows and data engineering systems.

Build and evaluate AI-generated responses related to ETL/ELT workflows and data engineering systems.Build and evaluate AI-generated responses related to ETL/ELT workflows and data engineering systems.

• Assess AI outputs for data accuracy, pipeline reliability, scalability, and workflow efficiency.

Assess AI outputs for data accuracy, pipeline reliability, scalability, and workflow efficiency.Assess AI outputs for data accuracy, pipeline reliability, scalability, and workflow efficiency.

• Assist in designing and implementing data systems and pipelines under the guidance of senior engineers.

Assist in designing and implementing data systems and pipelines under the guidance of senior engineers.Assist in designing and implementing data systems and pipelines under the guidance of senior engineers.

• Maintain and optimize existing data structures, ensuring integration with software applications.

Maintain and optimize existing data structures, ensuring integration with software applications.Maintain and optimize existing data structures, ensuring integration with software applications.

• Document data processes and adhere to data governance standards.

Document data processes and adhere to data governance standards.Document data processes and adhere to data governance standards.

• Support the data engineering backlog and contribute to best-practice implementation across projects.

Support the data engineering backlog and contribute to best-practice implementation across projects.Support the data engineering backlog and contribute to best-practice implementation across projects.

• Participate in technical discussions and contribute ideas to improve our data architecture.

Participate in technical discussions and contribute ideas to improve our data architecture.Participate in technical discussions and contribute ideas to improve our data architecture.

• Collaborate with software engineering teams and the Product team to ensure data solutions meet application needs.

Collaborate with software engineering teams and the Product team to ensure data solutions meet application needs.Collaborate with software engineering teams and the Product team to ensure data solutions meet application needs.