Data Engineer (Remote)

Darum lohnt es sich

About the Role Our client is seeking a skilled and proactive Data Engineer to join their fully remote, international team. This is an exciting opportunity to contribute to a data-driven organization, work with modern big data technologies, and thrive in a collaborative remote environment that values innovation and technical excellence.

Benefits • Competitive salary and performance-related bonuses. • Comprehensive health, dental, and vision insurance. • Flexible remote work arrangements and a focus on work-life balance. • Opportunities for professional growth and learning new data technologies. • A dynamic and collaborative team environment with a global reach.

This role, supporting data operations for clients originating from areas like Nelspruit, is essential for building and maintaining robust data pipelines and infrastructure that power analytics and business intelligence. You will work with large datasets, ensuring data quality, availability, and accessibility for data scientists and analysts.

Key Responsibilities • Design, build, and maintain scalable and reliable data pipelines and ETL/ELT processes. • Develop and optimize data warehousing solutions and data lakes to support analytics and reporting needs. • Ensure data quality, integrity, and security across all data systems. • Collaborate with data scientists and analysts to understand data requirements and provide clean, usable datasets. • Implement and manage data infrastructure using cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop). • Monitor data systems performance and troubleshoot issues to ensure optimal operation.

Requirements • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field. • 3+ years of experience in data engineering, data warehousing, or a related role. • Proficiency in SQL and experience with programming languages like Python or Scala. • Hands-on experience with cloud data services (e.g., AWS S3, Redshift, Glue; Azure Data Lake, Synapse; GCP BigQuery, Dataflow). • Experience with big data technologies (e.g., Spark, Hadoop, Kafka) and ETL/ELT tools. • Strong understanding of data modeling and database design principles.