Senior Data Engineer

📋 Description

• Design, implement, and sustain robust and scalable data pipelines utilizing AWS, Azure, and containerization technologies.

• Develop and manage ETL/ELT processes to extract, transform, and load data from diverse sources into data warehouses and data lakes.

• Collaborate with data scientists, analysts, and fellow engineers to guarantee seamless data flow and accessibility throughout the organization.

• Enhance data storage and retrieval performance by leveraging cloud services such as AWS Redshift, Azure Synapse, or other pertinent technologies.

• Utilize containerization tools like Docker and Kubernetes to ensure efficient deployment, scalability, and management of data pipelines.

• Monitor, troubleshoot, and optimize data processing pipelines for performance, reliability, and cost-effectiveness.

• Automate manual data processing tasks and enhance data quality through the implementation of data validation and monitoring systems.

• Establish and maintain CI/CD pipelines for automation and deployment of data workflows.

• Ensure adherence to data governance, security, and privacy regulations across all data systems.

• Engage in code reviews and ensure adherence to best practices and documentation for data engineering solutions.

• Remain updated with the latest trends in data engineering, cloud services, and technologies to continually enhance system performance and capabilities.

⛳️ Requirements

• Exceptional communication skills, particularly fluency in verbal English, is essential for explaining complex technical concepts to non-technical stakeholders and collaborating across teams.

• Demonstrated experience as a Data Engineer, with practical expertise in building and managing data pipelines.

• Strong knowledge of cloud technologies, specifically AWS (e.g., S3, Redshift, Glue) and Azure (e.g., Data Lake, Azure Synapse).

• Experience with containerization and orchestration tools such as Docker and Kubernetes.

• Proficiency in data engineering programming languages, including Python, Java, or Scala.

• Solid experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra).

• Familiarity with data processing frameworks such as Apache Spark, Apache Kafka, or similar tools.

• Experience with workflow orchestration tools like Apache Airflow, DBT, or comparable options.

• Understanding of data warehousing concepts and technologies (e.g., Snowflake, Amazon Redshift, or Google BigQuery).

• Comprehensive understanding of ETL/ELT processes and best practices.

• Experience with version control systems like Git.

• Strong problem-solving abilities and a proactive approach to troubleshooting and optimization.

🏝️ Benefits

• Competitive salary and flexible payment options.

• Opportunities for growth and professional advancement.

• Flexible working hours and the option for full remote work.

• Collaborate in an innovative, inclusive, and supportive environment.

• Be part of a data-driven culture that leads the way in innovation.