Data Engineer

Join our team as Data Engineer. In this pivotal role, you'll have the opportunity to harness the power of data to drive impactful solutions. Dive into the complexities of large datasets, design efficient data pipelines, and ensure the seamless integration of data systems that empower strategic decision-making. If you're ready to shape how data is stored, processed, and analyzed to unlock valuable insights and optimize business performance, this is the role for you. As a Data Engineer, you'll be responsible for building robust data infrastructure, implementing scalable solutions, and collaborating with cross-functional teams to transform raw data into actionable intelligence.

• Design and maintain robust, scalable, and efficient data pipelines to collect, process, and analyze large datasets from various sources.
• Ensure the quality, integrity, and availability of data by implementing best practices for data cleaning, preprocessing, and validation.
• Build and maintain data infrastructure, including data warehouses, lakes, and ETL processes, to support analytical and operational needs.
• Collaborate with cross-functional teams to define data requirements and implement solutions that address business challenges.
• Develop custom dashboards and visualization tools to provide actionable insights for internal teams and clients.
• Optimize database performance through indexing, partitioning, and query optimization.
• Implement and manage data governance policies to ensure compliance with regulations and data privacy standards.
• Stay updated with emerging data engineering tools and technologies, integrating innovative solutions to improve processes.
• Maintain comprehensive documentation for data workflows, pipelines, and systems.
• Train AI models, tune hyperparameters, and optimize model performance.
• Work with software engineers and product managers to integrate AI solutions into products and services.
• Stay updated with the latest AI research and trends, and apply innovative techniques to solve business problems.
• Monitor and evaluate the performance of AI models in production, making adjustments as necessary.
• Maintain comprehensive documentation of AI models, processes, and systems.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Proven experience in designing and building large-scale data pipelines and ETL processes.
• Proficiency in programming languages such as Python, Java, or Scala, with a strong focus on data processing libraries and frameworks (e.g., Pandas, Apache Spark).Expertise in database systems, including SQL and NoSQL technologies (e.g., PostgreSQL, MongoDB, Cassandra).
• Strong understanding of data modeling, schema design, and query optimization.
• Hands-on experience with data integration tools (e.g., Apache Airflow, Talend) and distributed systems.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and their data services (e.g., Redshift, BigQuery, Snowflake).
• Experience in building and deploying machine learning pipelines is a plus.
• Strong analytical skills, with the ability to work with complex datasets and derive insights.
• Excellent verbal and written communication skills, capable of presenting technical information to non-technical stakeholders.

• Social insurance
• Medical insurance
• Transportation allowance
• Education allowance

• Friday & Saturdays are off
• Hybrid workweek
• Flexible work environment with 8-hour workdays