Data engineer

The Data Engineer is responsible for designing, building, and maintaining scalable, efficient, and reliable data processing systems. This professional works closely with development teams, data analysts, and data scientists to ensure data availability and quality, as well as the effectiveness of analytical solutions.

Responsibilities:

1. Data Architecture Design: Design and develop robust and scalable data architectures that meet the organization’s needs in terms of data storage, processing, and access.
2. Data Integration: Gather, clean, and transform data from various sources, such as databases, file systems, APIs, and real-time data streams, for storage and analysis.
3. Data Pipeline Development: Create and maintain data pipelines for the ingestion, processing, and storage of large volumes of data, using tools and technologies like Apache Kafka, Apache Spark, Apache Flink, etc.
4. Cloud Data Management: Configure and manage data storage and processing services in the cloud, such as Amazon S3, Google Cloud Storage, Amazon Redshift, Google BigQuery, etc.
5. Performance Optimization: Optimize the performance and efficiency of data processing systems by identifying and addressing bottlenecks and failure points.
6. Data Security: Implement security and compliance measures to protect the integrity, confidentiality, and availability of data, such as data encryption, access control, and audit logging.
7. Automation: Automate repetitive tasks and workflow processes to increase operational efficiency and reduce the risk of human errors.
8. Interdisciplinary Collaboration: Work closely with development teams, data analysts, data scientists, and other stakeholders to understand project requirements and goals and ensure effective solutions.

Requirements:

• Bachelor’s degree in Computer Science, Software Engineering, Systems Engineering, or a related field.
• Previous experience in software development and distributed systems design.
• Deep knowledge of Big Data technologies and data processing tools, such as Hadoop, Spark, Kafka, Flink, etc.
• Familiarity with programming languages like Python, Java, Scala, or similar.
• Experience in designing and managing relational and non-relational databases, as well as using SQL and NoSQL.
• Analytical skills and ability to solve complex problems.
• Excellent communication skills and ability to work in a team.
• Preferably, experience in implementing cloud solutions, such as AWS, GCP, Azure, etc.