Data Engineer

Our requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
• Proven experience as a Data Engineer or in a similar data-focused engineering role.
• Strong programming skills in Python, Java, and/or Kotlin.
• Hands-on experience with Apache Spark, Hadoop, Kafka, Hive, Airflow, and SQL Server.
• Strong understanding of distributed systems, data architecture, and scalable data processing frameworks.
• Experience with software testing methodologies and automation frameworks such as PyTest or JUnit.
• Knowledge of containerization and orchestration technologies, including Docker and Kubernetes.
• Familiarity with modern CI/CD practices and tools.
• Strong analytical, problem-solving, and troubleshooting capabilities.
• Excellent communication skills and ability to work effectively in a collaborative, cross-functional environment.

Optional

• Experience working with cloud platforms (AWS, Azure, or GCP).
• Exposure to data lake, lakehouse, or modern data platform architectures.
• Experience with Infrastructure as Code (Terraform, CloudFormation, or similar tools).
• Knowledge of data security, governance, and regulatory compliance frameworks.
• Experience supporting machine learning or advanced analytics workloads.

Your responsibilities

• Design, develop, and maintain scalable batch and real-time data pipelines using modern data engineering technologies.
• Build and optimize data processing solutions leveraging Apache Spark, Kafka, and distributed computing frameworks.
• Develop and manage data warehousing solutions using Apache Hive and SQL-based technologies.
• Implement and maintain workflow orchestration using Apache Airflow, ensuring reliability and operational excellence.
• Establish and enforce data quality, governance, security, and compliance standards across data platforms.
• Monitor, troubleshoot, and optimize data infrastructure, pipelines, and processing jobs to improve performance and scalability.
• Design and execute automated testing strategies, including unit and integration testing for data workflows.
• Develop, deploy, and manage containerized applications and data services using Docker and Kubernetes.
• Build and maintain CI/CD pipelines to enable automated testing, deployment, and monitoring of data solutions.
• Collaborate with data scientists, analysts, product teams, and business stakeholders to understand requirements and deliver impactful data products.
• Document technical solutions, best practices, and operational procedures to support maintainability and knowledge sharing.
• Drive continuous improvement initiatives focused on reliability, scalability, and operational efficiency.

About the project

Benefits

• sharing the costs of sports activities
• private medical care
• life insurance
• dental care
• cafeteria benefits

COGNIZANT