Data Engineer @ Data Science UA

- 3-5+ years of experience working as a Data Engineer;
- Master’s or PhD in Mathematics, Cybernetics, Computer Science, or a related field.
- Experience building and scaling data pipelines on large tabular data using cloud and on-premises;
- Understanding data requirements from the DS team;
- Transforming raw data with issues into ready data for modeling;
- Experience working with temporal data and scraping;
- Experience of working with Python, PyTorch, Pandas, Oracle DB;
- Knowledge of cloud technologies, such as AWS and Python ecosystem;
- English - Upper-intermediate+.

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client:
Our client is a large-scale financial project with an extensive network and a strong market presence. The company manages vast amounts of financial data and is focused on enhancing its data infrastructure to support innovative solutions. With a commitment to long-term development, the team works on complex, high-impact projects — from optimizing data pipelines to implementing modern technologies across both cloud and on-premises environments. This is an opportunity to join a dynamic, data-driven company that values technical expertise and encourages growth.

About the role:
We are looking for a talented and passionate Data Engineer to join the team.

The company offers:
- Medical insurance;
- Laptop and cloud services by the company;
- Paid training, the opportunity to participate in the creation and publication of scientific articles (open-source knowledge development);
- Social package (paid sick leaves and vacation).

,[Design and implement scalable data pipelines for financial information processing using Python;, Design and support hybrid data infrastructure spanning on-premises and AWS environments;, Implement and support data integration solutions using tools such as Airbyte;, Ensure data quality, reliability, and system performance;, Collaborate with data scientists and analysts to optimize data delivery;, Establish best practices for data processing and documentation processes.] Requirements: Python, AWS, pandas, Oracle database

Kategorie

data

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